This startup looks to make batteries smarter and last longer with an AI based cloud platform [Interview]

Why Read This?

  • Learn about the how and why of battery management systems (BMS).
  • Find out about an Indian startup working on the software layer of battery technology with clients on a global scale.
  • Learn about the role AI can play in improving the life of a battery.

ION Energy is a Mumbai-based startup offering a range of battery management solutions aimed at improving the life and performance of lithium-ion batteries powering electric vehicles and energy storage systems.

This includes the ION Energy platform focused on proprietary battery management systems for lithium-ion batteries and Edison Analytics, a backend platform that combines battery data, analytics and AI to remotely monitor and improve battery life.

Having acquired Freemens SAS – a French battery management systems developer – in 2017, only a year after inception, the company says it now has a strong presence in SE Asia, North America and Europe with over 40 enterprise clients.

With a broad, global transition to electric, and with progress in li-ion being largely stagnant, the technologies that underlie battery management have come to the fore, aiming to allow OEMs, battery manufacturers, fleet operators and others to manage and improve battery lifecycles, reduce degradation, and ultimately positively effect their bottom line.

We spoke with Akhil Aryan, Co-founder and CEO @ ION Energy to find out more about the startup, the importance of battery management systems, their AI-based backend platform ‘Edison’ and the state of energy storage in India.


Could you give us a short intro to ION Energy and its history?

The energy space has always been very close to my heart. I believe that building, maintaining and optimizing the Energy Ecosystem is the greatest opportunity of our generation. Not only from a financial unit economics point of view but also environmental impact. 

I founded ION Energy in 2016 with a clear mission to accelerate Earth’s transition to an all-electric planet. ION is one of the world’s most advanced battery management and intelligence platform that is building technology for electric mobility and energy storage.

We initially started as a battery pack maker. We’ve built a few battery packs and the idea throughout was that in an ideal world you would be able to access the battery independently of a vehicle, just like when you use an ICE vehicle, you only pay for the distance you drive. 

Soon enough, we realized that if we wanted to make energy available as a service instead of an asset, we need to extend the life and performance of the batteries to make it a viable solution. That’s how we started designing our own BMS and found a few companies we could partner with. 

In 2017, we acquired an 8-year-old French Battery Management System (BMS) developer – Freemens SAS, in a first of its kind cross-border acquisition and started commercializing our flagship BMS platform. 

ION Energy Battery Management System Model ‘FS-LT’

Please shed some light on the importance of Battery Management Systems for our readers and how your offering stands out.

Electric vehicles are powered by batteries, which need careful monitoring and maintenance. They come with fixed lifespans, safe operating levels, and charge/discharge cycle track. Due to their high energy density, long lifespan and lightweight, Lithium-Ion batteries are favored by EV manufacturers.

Here, criteria such as voltage rating and Ah (ampere-hour) rating indicates when the battery must be charged. To attain higher voltage and Ah ratings, the cells are connected in series or parallel combinations. In fact, manufacturers often custom design the cell for improvising on application-specific characteristics.

Here is what really sets the battery of an electric vehicle apart from the fuel tank of a conventional vehicle: 

Firstly, safety. When operated at a constant voltage, while drawing large amounts of current, the temperature of the vehicle may sharply rise due to thermal runaway. Thanks to the volatile composition of a lithium-ion battery, it might even catch fire. This obviously risks the safety of the vehicle and passengers.

Further, the chemical composition of a Li-ion battery tends to deteriorate over time and intensity of usage. The charge/discharge rates, as well as the efficiency, begins to decrease with age and usage. When crucial performance parameters dip below/ shoot above normal value, the user must be notified. Thus timely repair or replacement can be initiated. 

With all these affecting factors, to preserve the health and lifespan of a battery, a battery management system is essential. If the battery is the heart of the vehicle, the BMS is its brain. It maintains optimum performance and notifies the user in case the health fails. It monitors various parameters to collect data for enhanced battery life and health. Be it simply alerting in case of under/overcharging, a sudden spike in temperature or a prediction for battery aging, a timely notification from the BMS can enable the user to take steps to prevent further damage.

Essentially, what ION does is that it offers the fundamental layer of battery technology & software that Battery Makers and OEMs leverage to build world-class batteries.

It is a battery management and intelligence platform with a focus on building technologies that improve the life and performance of lithium-ion batteries used in electric vehicles and energy storage systems. We leverage advanced electronics and software that accelerates the effort of engineering teams. 

ION Energy Battery Management System Model ‘FS-XT’

Tell us a little about Edison Analytics.

The life of a lithium-ion battery, on average, is up to 3 years or 500-700 charge cycles, after which, they need to be replaced. With batteries in modern EVs amounting to over 40% of the vehicle cost, there is anxiety around their life, performance (charging time, safety, etc) that requires more than just local safety protection. 

At present, the expected life of the battery is largely unknown and based on assumptions made by most companies. Because of the huge cost investment in li-ion batteries, it is critical to optimize the battery life, and the key to improving battery life lies in the data. By being able to remotely monitor, manage and improve battery life, Edison Analytics will make a data-driven case for consumers and fleet owners to choose EVs.

A full-stack advanced battery management and intelligence SaaS platform solution, Edison uses Data Science, Machine Learning, Digital Twin technology to determine, predict and exceptionally improve the life of lithium-ion batteries by up to 40%. 

A screengrab of ION Energy’s Edison Platform

What can you tell us about the AI part of Edison Analytics, which you say ‘improves battery life by 40%’?

Lithium-ion batteries today, are powering EVs, homes & large solar/wind micro-grids. They have one of the highest energy densities of any battery tech, a relatively low self-discharge, & require low maintenance, while on the other hand, they have a limited life that could be affected by usage, charging patterns and the environment in which they operate in, etc. 

On average, the life of a lithium-ion battery is up to 3 years or 500-700 charge cycles, after which, they need to be replaced. Today, the expected life of the battery is largely unknown and based on assumptions made by most companies. Since batteries amount to 40% of the actual vehicle cost, it becomes critical to optimize the battery life

We identified the underlying, core potential of battery data, leveraged it with machine learning, artificial intelligence & analytics to accurately determine, predict and improve battery life. 

Our battery intelligence platform Edison Analytics has been designed to use predictive intelligence and analytics to make sense of battery data and derive valuable insights, that can considerably reduce the overall ownership cost. 

Edison Analytics unifies data from the triple Es that majorly impact on battery life, i.e. entity (factors that are inside the battery), environment (factors that lie outside the battery but beyond the control of the user) and experience (dependent on user conditions). Edison amalgamates and assesses the data from these three sources to to customize the life and performance.

Edison uses real-time simulations and visualizations to accelerate deployment speed, data analytics to improve uptime, and machine learning to improve battery life. It ingests and analyzes data sets to identify what factors are contributing to abnormal degradation of health and what is their magnitude of contribution so that businesses can take appropriate actions like configuration changes over the air, drive profile changes or environment changes to extend battery life by up to 40%. 

A screengrab of ION Energy’s Edison Platform

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How did you go about choosing to go down the SAAS route as opposed to bespoke deployment?

Bespoke software development has advantages like ability to customise or tailor make the solution to fit the exact need of the customer. In case of Edison Analytics, it would mean developing the exact analytics, reports and insights which a particular customer would look for.

We took the SaaS approach with this flexibility in mind. Edison Analytics allows the user to customise the software by making changes to the model, dashboards, reporting and insights to make it fit their needs, but without having to build a costly bespoke software.

Thus Edison Analytics carries the advantage of a flexible solution without increasing the costs. 

Would it be safe to say that the software and BMS layer of battery technology is where innovation is truly happening, considering progress in li-ion seems stagnant? Is that impression correct?

Batteries contribute to 50% of the total cost of an electric vehicle. These include: 

  1. Cells: Practically a commodity, cells have a similar power and energy capacity, are engineered by many brands in the market and made available for all battery makers. 
  2. Battery pack assembly: Battery pack manufacturing is simply an assembly and design function. The packaging is offered by all battery makers and only differs as per the needs of the application 
  3. BMS & Software: This is where innovation truly happens. In an electric vehicle, the battery management system and software are the core differentiators between battery pack makers. The ‘brain’ of the battery – BMS and the software is responsible for safety, communication, performance, and better battery life. The software constantly helps monitor key parameters like the State of Charge (SoC), State of Health (SoH), residual life, etc, to gain key insights into the health of the battery. 
‘ION Trace’ – A companion app to track the lifecycle of assets.

How has your experience been working with a number of industry behemoths?

We’ve had a brilliant experience working with enterprise customers and a majority of customers are committed towards accelerating the all-electric transition.

Working with large enterprises has enabled our Battery Management Systems to become versatile and multi-functional across applications (low voltage to high voltage) and lithium-ion chemistries.

We’ve taken up electrification projects with OEMs to help them explore multiple lithium ION chemistries. Since our products are chemistry agnostic we are helping them to benchmark different chemistries and their performance. Our Platform has helped our clients scale up their battery deployments faster and reduce time to market.

Have you deployed your technology to non-vehicular environments like microgrids? What is the state of energy storage in India in that regard?

We have deployed our platforms in other sectors like Energy Storage, Telecom, Defence, etc.

At present, more than 90% of the ESS (Energy Storage Systems) market in India is completely driven by government policies.

As per the ISGF report on Energy Storage System in India – roadmap for 2019-2032, the total requirements of ESS for grid support is 17 GWh by 2022, for e-Mobility is 40 GWh and total from all sectors is 178.5 GWh by 2022. Depending upon the overall economic growth and development of the infrastructure sectors, this could be certainly above 100 GWh.

Most of these are likely to be imported. The cumulative demand of ESS by 2032 estimated is in excess of 2700 GWh which is a strong case for setting up of giga-scale battery manufacturing plans in India on fast track. [Source]

What is your take on the current government policies towards the EV ecosystem?

Government policies are paving the way and playing an important role in the all-electric future by encouraging electric vehicle adoption, enabling faster deployment of charging stations and improving affordability. The push for Electric Vehicles in the country is truly commendable.

It’s important to encourage localisation of battery technology and not be reliant on China and other countries as lithium-ion batteries amount to a significant cost of an Electric Vehicle.

GoI seems committed to developing the complete EV ecosystem that includes charging infrastructure, manufacturing batteries and other components domestically, which is definitely the need of the hour. 

What’s next for ION Energy?

ION is building a core layer of infrastructure to enable electric mobility and clean energy adoption in Asia with a focus on India. We are aiming to rapidly expand our global operations to 20+ countries and set up new branches in the USA and Bangalore. Our target is to sell over 50,000 BMSs and have upwards of 1GWh of batteries under management on the platform by 2020.


[Interview] Fast, furious & electric? Emflux Motors is building India’s first ‘electric superbike’.

Why Read This?

  • Learn about the fledgling two-wheeler EV space in India.
  • Find out about Bengaluru based EV startup Emflux Motors which is building India’s first ‘electric superbike’ with a claimed top speed of 200 kmph.

While most electric vehicle startups globally, and in India, are concerning themselves with solving purely the functional problems of commuting and short distance intra-city travel, Bengaluru-based EV startup Emflux Motors has chosen to go a little offroad. Founded in 2016, Emflux Motors have set themselves about tackling the more rarified desire of those who ride for pleasure, speed and an adrenaline rush (Indian roads might be inclined to blush here) – superbike enthusiasts.

The Emflux ONE, Emflux Motors’ ‘electric superbike’, is claimed to go from 0 to 100 kmph in 3 seconds, with a top speed of 200 km/h along with a range of 200 km on a full charge. If those numbers weren’t impressive enough, the bike also boasts custom performance biking parts from brands like Ohlins, Pirelli and Brembo which are commonplace on traditional ICE (internal combustion engine) superbikes.

While the Emflux ONE is still in a pre-production prototype phase (expected launch in late 2020 in limited numbers), we figured it would be worthwhile to learn more and caught up with Ankit Khatry, COO & Co-founder, Emflux Motors for a chat about the bike, the team behind it, and the challenges in building an electric superbike as a startup in India.

For those who’re unaware, could you give us a short intro to Emflux Motors and its history?

Emflux Motors was founded in August 2016 by the confluence of a common vision shared by three guys from very different backgrounds – myself, Varun Mittal and Vinay Raj Somashekar. Emflux aims to build products and services which are desirable, meaningful, and come with zero compromise on the quality and the vision they are based on. These qualities are willed into the avatar of our first product – The Emflux ONE – an electric superbike that is capable of accelerating from 0 to 100 km/h in 3.0 sec, has a top speed of 200 km/h, and a city range of 200 km on a full charge.

How did you hit upon the idea of performance biking in the EV space and what were the initial challenges?

The whole idea of building a high performance vehicle was to demonstrate the tremendous potential of electric technology not only in terms of performance, but also in terms of ruggedness, reliability, and of course, range.

The performance bike segment also is seeing a high rate of growth in India. These reasons coupled with the fact that the high cost of Li-Ion cells wouldn’t make economic sense for us is what drove us to build a full-blown Electric Superbike instead of a run of the mill commuter or some semi high-performance motorcycle.

Tell us a little about the Emflux One.

Emflux One is an electric superbike and a flagship product of Emflux. It’s insane acceleration of 0-100 km/h in 3.0 sec coupled with a top speed of 200 km/h and a city range of 200 km should rest any and all apprehensions that people may have about electric vehicles.

Our technologies are indigenously developed in order to get better integration and full control over the bike which will increase its efficiency and deliver better performance overall.

While many of the parts in the bike are sourced from leading names, you have also built a number of components in-house, like the EVSE (Electric Vehicle Supply Equipment). Tell us about those. 

Barring the Brembo brakes, the Ohlins suspension, Pirelli tyres, some small accessories, and the individual Li-Ion 18650 cells, every single component on the Emflux ONE has been conceptualized, designed, and engineered in-house.

This includes the entire styling design, the mechanical structure, the motor, the drivetrain, the battery pack, and all the technologies such as the BMS, the Motor Controller, the Charger Circuit, the Master Controller, and also the wall-mount charger or EVSE. These technologies can be up-scaled or down-scaled to fit any sort of EV. In fact, we are finalizing talks with several OEMs as well as EV start-ups for design and development of their technology, mechanical, and styling design.

Where are you currently at in terms of manufacturing and launch?

Our pre-production prototypes are undergoing rigorous testing on our test-benches and out in the real world. We have achieved 70-80% of our claimed acceleration figures during our test runs of the newest prototype.

The production-ready version of the bike should be ready mid-next year, and following homologation and certification, we should be able to deliver the first Emflux ONE to our customer in 15 months.

What changes to the standard electric two-wheeler engineering stack does the performance biking aspect entail?

There are minor changes to the architecture of the vehicle, but as such, the stack is quite similar. Obviously we have had to design each and every component for much higher current and voltage levels.

For example, our motor and motor controller is rated for twice the voltage and five times the current of the best electric scooter available in India. Also our motor peaks at 16,000 RPM which is much faster than any other two-wheeler.


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How do you intend to position, market & service the bike considering the premium price tag? Would it be via the traditional route of setting up showrooms or something else?

We have received overwhelming responses to our social media posts and in emails from the people of our country as well as outside the country.

We will be having an experience center in Bangalore, followed by other metro cities. A customer can walk into our experience center and know more about the bike. Some customers can test our bike on track days (invitation only) which we will have across different cities. Purchases would be completely online through our website via digital payment methods.

Our bike will require minimal service, and any services required will be done at the customer’s home or at any place that the customer chooses.

Your vision statement mentions that you would like to become a technology and component supplier to OEMs. In that context, is the Emflux One somewhat of a proof-of-concept? Is the long term plan to strengthen & license your technology IPs?

The Emflux ONE will be our first full-blown product for the world. The key strategy is to create a high-end product in order to create a brand image as well as to support initial production capabilities, following which, we will introduce higher volume mid-segment products into the market. We are finalizing talks with several OEMs as well as EV start-ups for design and development of their technology, mechanicals, and styling design. Maybe in the future, we can see the market of components supplier as an opportunity, but we will have a separate subsidiary for that. Emflux will only cater to the premium electric bikes segment.

Tell us about your rather funky looking ‘Master Controller’. What ‘smart’ features and information can a rider expect from it?

The dashboard will be based on what we showcased in Auto Expo’18 but will have a much cleaner, more intuitive, and better designed interface. Apart from the standard smart features that are available on most smart EVs today, we will have some very cool and useful features which will set our bike apart. We want our users to have a better riding experience than any bike out there in the market today.

What’s your take on the government’s current policies towards the EV ecosystem?

The category for Emflux One will not fall under FAME subsidies for now. However, the good thing about the policy is that the Indian government is supporting hardware manufacturers. It will help India grow as a full-fledged automobile manufacturer and cement its position as one of the leading nations in the world in this regard.

How do you see the two-wheeler EV segment in India playing out over the next few years?

Even though there are a lot of EV startups in India doing incredible development work, lack of funding is hindering their growth. We believe that, ultimately, one or two startups will succeed in becoming OEMs over the next 10 years.

We feel that the EV market will play out like the mobile phone market and Chinese EV startups will give tough competition to the established OEMs in India. As far as we know about the internal EV programs of these OEMs, they have a lot of catching up to do.

What’s next for Emflux Motors?

We are progressing well in terms of in-house R&D, however, lack of funding is slowing down our progress considerably. Should we overcome this obstacle, the launch of our products will be in phases. The Emflux One will be limited to 200 numbers for India. The Emflux Two, a mid-performance two-wheeler, is being designed for higher volume manufacturing and sales. In parallel, we have started selling different EV components and products that we have made for ourselves. These include our Automated Spot Welder (used to spot weld nickel strips to battery cells to make battery packs), a Cell Penetration Test Bench, Two-wheeler EV Dynamometer, Wall Mounted and Portable EVSEs which are more cost-effective and better in many aspects than products available in the market. We are looking to sell these products to other startups and established companies.

Why should all electric vehicles look like bulky sedans? Meet Strom Motors’ funky 3-wheeled electric car.

Why Read This?

  • Learn about an upstart firm aiming to compete in the Indian four-wheeler EV space.
  • Take a look at India’s first passenger vehicle with a unique ‘reverse trike’ arrangment – two wheels at the front and one at the rear – to have gained ARAI approval.
  • What does designing an electric vehicle for urban India mean?

Strom Motors is a Mumbai-based EV startup working on building made-in-India ‘urban mobility solutions’, the first of which is an electric car with a rather unique ‘reverse trike’ arrangement called the Strom-R3. In a ‘reverse trike’ structure, the vehicle has two wheels at the front and one at the rear. Having recently received ARAI (Automotive Research Association of India) approval – making the Strom-R3 the first Indian passenger segment vehicle with this arrangement to do so – the company is currently in the process of setting up manufacturing and gaining other government clearances.

We spoke with Pratik Gupta, Founder & CEO @ Strom Motors, to learn more about the startup, the Strom-R3, its standout features as well as his take on some of the challenges for EV in India currently.


The Strom-R3 electric car.

For those who’re unaware, could you give us a short intro to Strom Motors and its history?

Strom Motors is a wholly owned subsidiary of E14 Technologies Pvt Ltd, a Mumbai based RnD company (founded in 2011). The original founders of the company have a combined RnD and product building experience of over 75 years. Strom Motors is a result of an internal RnD project, where we identified that the new-age automobile customer is completely different than what car companies are building for.

“Shared mobility and minimal carbon footprint are now front and center issues of urban consumers, while big and bulky Sedans & SUVs are not so attractive to millennials; who do not wish to spend a large part of their paycheck towards a vehicle that is not used much.”

Tell us a little about your electric car – the ‘Strom-R3’ – its variants and its standout features.

Strom-R3 is an urban mobility solution which is 100% electric and provides a safe and air-conditioned comfortable cabin for two. Strom-R3 is designed and built for an urban user of any modern city around the world. We foresee three major market segments using this platform –

  • the daily office commuter who is looking for a quick and safe vehicle around town
  • as an additional car in the family for running errands around 10km radius
  • first/last mile shared mobility solution parked at metro stations and bus stops
The Strom-R3 with a ‘reverse trike’ arrangement.

It has been said that the car has been designed specifically for India’s urban areas. What does that mean in terms of feature design?

The Indian consumer, as we all know, is extremely value driven and not price driven. With Strom-R3 the focus was to cater to particular needs to our target audience and just concentrate on price reductions.

Some of the major design decisions we took early on revolve around how we foresee the eco-system evolve. Given the condition of power distribution and parking issues in India, for mass adoption compact mobility solutions (2 and 3 wheelers) can only hit mass volumes if we shift to swappable battery solutions.

Given that Strom-R3 battery requirements are fairly small we have designed the batteries to be modular and installed under the bonnet of the car making them easier to swap compared to a typical car which has them as part of the floor of their entire car length. Using modular batteries also come in handy during middle-of-the-road stranded situations where mobile support vans can replace a few battery packs to help the user reach their destination. Some of the other aspects revolve around ease of use like having both front and rear storage, multiple LCD displays with fully customizable UI for dedicated and personalized interfaces.

“In future, we also plan to offer semi-autonomous features like ability to follow the vehicle in front of you at speeds less than 25kmph to avoid stresses of stop-and-go traffic which are common in most cities. Remote phone controlled driving for tight parking spots where opening a door is not a possibility and users can remotely drive the car into the spot.”


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The Strom-R3 has – for the Indian market – quite a unique ‘reverse trike’ configuration. What are the benefits of such a system and why did you choose to go ahead with it?

I am glad you asked this. With current li-ion battery prices, extra weight on the car means you require bigger battery which then raises product pricing and operating costs. This is the main reason behind the fact that current EVs on the market costs over Rs.10L and only go for 120kms. With an average occupancy of 1.6 in cities, urban consumers are looking for a compact two-seater solution which is affordable and easy to park.

Three-wheeled reverse trike platform fits perfectly for this need and provides similar stability as a hatchback while reducing weight by almost half which increases drive efficiency by three times. This directly translates into extremely affordable prices for 200kms on a single charge and about Rs.0.40 per km.

Where are you currently at in terms of manufacturing and launch?

Strom-R3 was unveiled in April, 2018 in Mumbai and has received a lot of excitement and support since. We are currently setting up our manufacturing and the vehicle itself has recently passed government approvals. We will announce launch and availability dates soon.

How do you plan to deal with the charging infrastructure paucity in India at the moment?

Strom-R3 will come with three range options of 120/160/200 kms per charge. Given that the platform is designed for urban usage, most use cases involve a daily driving distance of 20-100kms.

“We expect bulk of our users to charge at home or office and never having to depend on public charging infra. Having said that, this does limit us currently to users with fixed parking spaces at home or work, but we believe as the eco-system develops swapping solutions will become ubiquitous.”

Till then, with an onboard charger that takes 3 hours for a fully depleted charge cycle users can charge at any location with a 15Amp single phase power supply (most hotels, restaurants offices etc). We are also compatible with almost all publically available charging infra that is coming up around the country and even in future, will support our users if standards change.

‘Smart’ vehicles is the ‘in’ thing at the moment. Are there any web and mobile connected features in your vehicles worthy of mention?

We take the term “Smart” very seriously and for us, it just does not mean that you can track your car or turn your AC, lights using an App. Strom-R3s come with 4G connected diagnostic engine where users can track not just location and status of charge but can also get a complete health report of critical components like brake pads, motors and electronics. The new Indian consumer expects these features as standard fitment rather than pricey upgrades.

“EVs can use upto 20% extra energy while going over bad roads or rain affected conditions. The on-board system continuously tracks the road terrain and driver habits along with machine learning based navigation engine to learn your daily drive routes and help with intelligently predicted real-world range rather than a State-Of-Charge based range estimation.”

This data rich system also feeds into our citywide database to help other Strom users with alerts about impending bad roads resulting in lower than expected driving range so that they can plan accordingly rather than being stranded in the middle of the road.

Some of these features will be made available directly through the on-board touch screen interface or via the Strom Connect App. For us Smart means providing users with smart insights and actionable inputs.

What is your take on the government’s current policies towards the EV ecosystem?

We welcome the positive initiatives that the government has taken so far especially with awareness and urgency to convert to EVs. India being a diverse democracy, things sometimes take time to get implemented but the current transparent and corruption free environment really helps startups like Strom to compete on technology and product value rather than company size, political tie-ups and family backgrounds.

As the market matures, Indians will have multiple choices and more evolved products on offer. It is similar to the radical change that cellular phone industry went through where after the launch of app based software driven phones, the industry grew from two or three major manufacturers to over 50, each with better and more nuanced product offering catering to larger part of population.

What’s next for Strom Motors?

Currently we are working tirelessly to bring Strom-R3 to market and expand to multiple Indian cities. We are also in discussion with some European companies to take Strom to global cities. On the product front, we are working with IIT, Mumbai’s Industrial Design Center to design inner-city delivery van on the same platform for a clean and efficient logistics delivery market. Looking forward to the exciting opportunities that Indian market now offers.

Your need for speed can be electric. Meet Ultraviolette Automotive. [Interview]

Why read this:

  • Learn about the emerging two-wheeler EV space in India.
  • Ultraviolette Automotive happens to be one of the most exciting amongst them, on the verge of launching the fastest 200-250cc equivalent electric bike in the country.
  • What does it take to build a high performance electric two-wheeler from scratch?
    Find out.

Ultraviolette Automotive is a three-year-old Bengaluru-based EV startup that is close to launching their first two-wheeler, the F77 – a premium electric bike, equivalent to a 200-250cc motorcycle, claimed to be the fastest in its category. Backed by TVS Motors, the startup aims to fill the gap of providing a high-tech power-packed and power-efficient alternative to ICE (internal combustion engine) two-wheelers in the premium category.

One of the interesting things about Ultraviolette Automotive is the fact that they seem to be working on a lot of components from the ground up, with 9 international patents for their battery technology alone. And apart from the standard ‘smart’ enabling bells and whistles that are seemingly accompanying every new two & four wheeler, the company seems to be expending a lot of smarts on engineering their bike. Which makes them truly worth watching out for.

We caught up with Narayan Subramaniam, CEO & co-founder of Ultraviolette Automotive, for a chat on the F77, the state of EV in India, and how he sees the government’s policies towards EV right now.

(L-R) Narayan Subramaniam, Chief Executive Officer along with Niraj Rajmohan, Chief Technology Officer of Ultraviolette Automotive.

For those who’re unaware, could you give us a short intro to Ultraviolette Automotive and its history?

Our goal at Ultraviolette Automotive is to accelerate the adoption of electric vehicles – in India to begin with. This is the vision we started with, and it made sense to start with two wheelers because typically, for two-wheelers, the product development timelines are in the range of 2.5 – 3 years.

“One of the major concerns that we at Ultraviolette Automotive are addressing is the fact that the entire electric vehicle industry in India has always been associated with low performance and a zero desirability quotient. Today, we are living in times where all forms of vehicles come with a certain pride of ownership. Right from the first bicycle you want as a child, the motorcycle you want to ride in college, to the car you aspire to own later in life.”

At Ultraviolette Automotive, all our products and solutions are designed and developed with a single-minded focus towards delivering high levels of performance and unparalleled user experience across the usage and ownership experience cycles. In essence, a completely new identity for electric vehicles.

Now coming to the other side of the equation – energy. We realized very early on that a good product alone will not accelerate the transition towards electric mobility. There needs to be reliability and predictability built around the availability and usage of energy. We have spent considerable time and built a lot of IP around the development of batteries and various forms of charging technology that will soon become a crucial part of the electric ecosystem.

f77_ultraviolette
Ultraviolette Automotive F77 Electric Bike.

Tell us a little about the F77 and its standout features.

India represents a very unique and interesting culture, when it comes to vehicles. Premium and performance oriented products are seeing a steady rise in demand. Today, we are far more connected and aware of the world than ever before, thanks to the insanely accelerated development in the electronics industry. So, why not the same when it comes to our vehicles.

“I believe that it is about time we create and offer world-class technology in the two-wheeler space as well. Any vehicle we own, is seen as an extension of our personality. And it is this unique culture that we are addressing with the F77.”

The F77 is a high-end technology oriented, high performance electric motorcycle. It has been developed ground up, with principles used in the aviation industry – right from the advanced engineering simulations, multi-level safety systems to the design identity of the motorcycle. It is an urban sports motorcycle with a battery range in 3 digit figures 0-100 kmph in sub 8 seconds and a power output to the tune of 25 KW.

The F77 is a smart and connected electric motorcycle that comes with remote diagnostics, over-the-air (OTA) upgrades, regenerative braking, multiple ride modes, bike tracking, ride diagnostics and a whole lot of other features.

Why has the power-packed + power-efficient combination been so hard to crack for the two-wheeler EV industry so far?

There are 2 parts to this answer:

Electric two-wheeler markets and their perception:

“There has been a lot of development in power-packed and efficient electric four wheeler technology in various parts of the globe. There is a lot to be learnt from how companies like Tesla have tackled various problems, right from technology, to the business side of things.”

However, when it comes two wheelers, there are a very few companies worldwide working on performance oriented motorcycles. This is largely due to two factors: 

  • In the western world, the two wheeler segment is predominantly a recreational and an enthusiast segment. These segments are not large enough for companies to achieve economies of scale.
  • In the east, electric scooters have become the lowest common denominator when it comes to commute. There are vehicles being operated under various kinds of business models, that are not necessarily ownership based. Hence, these scooters are devoid of any emotional attachment (pride of ownership).

India however, represents a very different market with a different mindset. Pride of ownership is an important factor, as are aspects like performance, technology and style, when it comes to purchasing vehicles.

Technology barriers that come with the development of high performance vehicle:

“Building a high performance motorcycle comes with no shortcuts, and neither are there enough benchmark vehicles to learn and improve upon. What we had to do was start the development of the motorcycle from ground up – right from the chassis and a new architecture for the motorcycle to the battery tech that can deliver the kind of energy required, keeping multiple complex safety constraints and harsh Indian conditions in mind.”

Having had to redefine the fundamentals, there were a lot more supporting components that had to be developed as they simply did not exist. For this, you need an accomplished R&D team, both on the mechanical and electronic systems front, without which building this sort of vehicle would not be possible.

I believe these are the major reasons as to why this segment has seen less action and most (not all) companies have tried avoiding this loop of R&D and have chosen to enter the market with lower powered electric vehicle kits.

Ultraviolette Automotive Battery Pack.

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You seem to have a full stack approach to building your EV ecosystem – extending to innovating on your batteries as well. Could you shed some light on this?

Using two wheeler battery packs imported from SE Asia comes with critical drawbacks as they are not built for aggressive Indian usage conditions. Most of these battery packs are not developed to operate at the kind of temperatures we see on a summer day (read 45 deg +) and neither are they designed to offer the durability and reliability to last the average ownership cycle of a two-wheeler in India.

Most importantly, safety is a critical aspect that is often not addressed, especially when it comes to Indian conditions. They do however, serve the purpose of low powered, low range applications. But this is far from what you require for a full blown, performance motorcycle.

There are a few companies across the world that make Li-ion cells. Engineering of the battery pack is the most crucial aspect when it comes to optimizing the energy available from these cells.

“Our crucial efforts in the R&D have been around thermal management, safety loops across mechanical, thermal, electrical and software systems and we have done several months of testing and iterative improvements to meet the aggressive requirements we started out with.”

For instance, today we are running our production ready 10th generation of the battery management system.

Where are you at currently when it comes manufacturing and launch?

Our production ready prototypes are now going through various forms of testing and we looking to launch our motorcycle towards the end of 2019. 

Your partnership with TVS Motors must provide you with access to some serious expertise in building two-wheelers. Tell us a little about it.

“We see long term synergy when it comes to our association with TVS Motors, considering the rich heritage and decades of industry experience that TVSM brings and the innovations in design, technology and business at Ultraviolette Automotive.”

Ultraviolette Automotive Charger.

What is your take on the current government policies towards EV?

It is commendable to see the government being pro-electric and addressing sustainability at a both at a central and state level. We think there has been significant development in laying the foundation for EVs and the eco-system. There are several factors that will contribute to the exponential growth of EVs across India.

Standards around charging infrastructure have been finalized this year and we should start seeing a push towards nationwide deployment of charging infrastructure. Apart from this, we have seen a clear indication of renewed subsidies through the FAME program.

“Overcoming range anxiety is the real issue here. At the outset there are two ways to deal with this problem. First, by providing a significant range – sufficient to cover the heaviest usage scenarios. Second, by building a network of energy stations that would provide access to energy on-the-go. We believe a combination of both of these approaches will support the growth of EVs.”

However, we are still at a nascent stage and with time and increased adoption, there will be well rounded-policies right from manufacturing support to customer incentives.

ultraviolette_automotive_app
A mock-up of the app accompanying the F77.

What’s next for Ultraviolette Automotive?

Our goal is to help influence our country and in due course of time, the world, to move towards a smarter and more energy efficient future and we will keep pushing boundaries on this front. The F77 is what we hope will create a new identity for EVs, dispel any myths associated with EVs and kick-start this revolution.

How do you see the two-wheeler EV segment playing out over the course of the next few years?

“Electricity as a form of energy in the transportation space, is here to stay. It is no more a question of ‘is it going to be electric’, it is more of ‘how soon’. The electricity grid is already in place across the planet and operates at a significantly higher efficiency than any other currently available form of energy distribution and storage.”

With regard to the transportation industry, I believe this will carve out multiple interesting use cases for vehicles and foster new business models as well.  Both consumer owned as well as shared mobility use cases will rise, and new segments could arise as well. 

Electric is inherently suited for both ‘stop and go’ traffic scenarios and for pushing the boundaries of ‘high performance’.


Nir Iyal on Indistractable: The opposite of traction is distraction [Interview]

Hooked author, Nir Iyal’s next book Indistractable has been released and we had an opportunity to read the pre-launch copy (review soon).

Indistractable How to Control Your Attention and Choose Your Life

In his new book, Nir Eyal describes how to manage the discomfort that drives distraction, and explains why solving the problem is not as simple as swearing off your devices.

With a four-step, research-backed model, indistractable lays bare the secret to getting the best out of technology, without letting it get the best of you.

Empowering and optimistic, this is the book that will allow you to control your time and attention – and live the life you really want.

But then, we had quite a few questions for Nir Iyal, especially when Hooked was all about creating sticky products and Indistractable is all about letting go of those sticky products.

So here is an interview with Nir Iyal on his take on distraction vs. traction and why people need to be a little more thoughtful about what they are consuming.


From hooked to Indistractable: This is a complete role reversal. What prompted you to write this? 

Nir Iyal: It’s not really a role reversal. I think I have a very unique position that I know the inside of how these products are built and who better to tell you the achilles heel of how to fight distraction than someone who understands how these products are built to hook us. We can put distractions in their place while still getting the best of technology without letting it get the best of us. And so there’s really no dichotomy here. We should use habit forming technologies for good and help people build healthy habits while still being careful of not letting these technologies become distractions.


Majority of people are struggling to have the financial freedom and sometimes, books like these make one feel that it is only written for those who have achieved financial freedom and are in a position to ‘choose’ their distractions! What are your thoughts? 
Nir Iyal: No, I don’t think so at all. So, we need to first understand the difference between distraction and traction. Traction is anything that you plan to do with intent. Something that you that moves you towards what you want in life.

The opposite of traction is distraction. So, it’s anything that pulls you away from what you want to do in life. And this doesn’t require any money or particular financial resources if you find yourself distracted at work or at home, or with your kids and your personal life. It doesn’t matter where you come from. It has nothing to do with money whatsoever and I can’t see how it does.

To be able to learn the skill of the century – to be able to control your attention and choose your life. In many ways, those who are less financially secure need this more because this is how we get ahead. This is how we enjoy our lives and when we’re with our family as well as do our best work at work by being truly focused on whatever it is we’re working on. So, if what you want to do with your time is to do your best work, I’m going to help you do that. If what you want to do with your time is to be  with your family in your off time, on weekends and evenings then I’m going to help you do that as well. Whatever is consistent with your values.


I am guessing that you meditate a lot. Could you share your perspective / process here? 
Nir Iyal: No, I don’t meditate at all. And I tried it for about a year, didn’t really do much for me and I’m not saying that people shouldn’t meditate. If it works for you, great, keep doing it. But, I don’t talk about meditation in the book at all other than to say I won’t be talking about it. Because, I think it is a little bit overdone.

There are so many books about it already. Again, not that it doesn’t work. It can be extremely effective for people who actually do it but what I find is a lot of people don’t have the ability to fight distraction long enough to actually meditate. So, if what you want to do is to meditate, I’m going to help you with this book and make sure you do that.


To the creators out there –  would you still recommend reading ‘Hooked’-  and create sticky products ? 🙂 
Nir Iyal: Absolutely. We can create all kinds of habit forming products to help people improve their lives. Product like Kahoot which has used the hook model to build habit forming products for children in school.

Products like Fitbot which helps people build healthy exercise habits in the gym. That’s a great habit. All kinds of habits that we can use to help people exercise more, eat right, be more productive at work. We can still use these techniques for good and anyone who is in business looking to improve their customer engagement and retention should still read Hooked.


Your perspective on price pacts / identity pacts still require one to have a habit (i.e not press the snooze button) – where does one start with, if one isn’t so motivated (which is the case with 99% of the world)? How have you achieved this?  

So, you’ll remember that the price pact and identity pacts come last in the book. So, this is what we do after we’ve learnt to master the internal triggers and after we’ve learnt to make time for traction – after we’ve learnt to hack back external triggers. That’s where we start with the first 3 steps. Never ever jump into the fourth step or it will backfire!


Go ahead and grab your copy of Indistractable, if you haven’t.

Junglee Games: We are $600mn in Annual Gross Gaming Revenue [Interview]

 Junglee Gamesthe fastest-growing skill-gaming platform, has reached the 25 million users milestone, and is leading charts in the top skill-based games in India.

The company has more than doubled its player base in the last 6 months and has grown from 10 million players last year to more than 25 million players today. 

While building games that entertain the masses, Junglee Games goes way beyond being simply another gaming company. Junglee Rummy, the flagship product of Junglee Games, has seen a meteoric rise in its user-base growth across the nation with its innovation, value-driven culture, and the amazing user experience it creates and offers. 

Ankush Gera, Junglee Games CEO
Ankush Gera, Junglee Games CEO

Here is a QnA with Ankush Gera, founder and CEO of Junglee games where we explore the changing landscape of skill gaming in the country and how Junglee uses various product-driven strategies to acquire, retain and engage users!

NextBigWhat: What are some of the key metrics on revenue vs. users at Junglee?

From 2013 to 2019, we’ve close to doubled in revenue and player count every year. We started off with a player base of less than 1 million, which has today grown to 25 million users. And our growth trajectory shows that we will reach 40-50 million users by the end of this fiscal year.

This is also reflected in our Annual Gross Gaming Revenue. In the year 2013, our Annual Gross Gaming Revenue was $10 million and today we are at $600 million and growing exponentially.


NextBigWhat: Before Junglee, you were running a consulting services business (Monsoon). How did you shift the gears from a service business to a product business? What were some of the core lessons learned, which other entrepreneurs who are in similar shoes can benefit from?

The consulting business allowed conceptualizing to delivering several hundred products over a decade. We saw the transition from the desktop to the mobile in its early days. Aggressive timelines, exposure to fortune 100 clients like HP where our apps shipped on tens of millions of devices, and being on the cutting edge of marketing, data and product development, alongside managing teams both internally and externally, made the transition relatively easy.

In fact, the catalyst to starting Junglee was having full, end-to-end ownership of products beyond launch and turning products into businesses. There were a lot of lessons learned around always owning our own intellectual property versus licensing and being at the mercy of others, not tolerating people who were skilled but culture misfits, investing in data science early on and the biggest one being diversification.

Everyone knows about the successful exit to Capital One but Monsoon almost went out of business twice because we had a lot of revenue from just 1-2 clients and we weren’t diversified enough. We were very fortunate to have weathered two big storms.

At Junglee, we’re operating different games across different markets to ensure we’re well diversified.


NextBigWhat: How has the skill-gaming ecosystem in India developed as opposed to China and the US? Where do you think are big opportunities?

India presents a massive opportunity. The biggest difference in comparison to China and the US is that while those markets have established ecosystems, the Indian market is still at a very early stage. We have over a billion people, a large chunk of the population using affordable smartphones and data, just getting used to micro transactions and very little forms of entertainment. There are opportunities in skill games, e-sports and eventually freemium as well. Educational games and generally gamified applications also present a big opportunity.


NextBigWhat: How do you focus on user retention? Are there any specific tools or processes you use?

User retention, particularly in the gaming industry, is of the utmost importance, and we take it very seriously. We approach user retention in two ways — one through a cross-channel marketing automation tool where we target users on the basis of their playing patterns like the time spent on the app, platform affinity, etc.

We reward regular users with loyalty points that can be used for playing cash games and redeemed for bonuses. We run big tournaments on a daily basis to ensure that a user can derive some value from Junglee Rummy every time they log in. 

The second method is our Customer Success team, which ensures that any issue that a customer faces is resolved within 24 hours. That ensures customer loyalty in the long run.

We also take special care by talking to the user in their preferred language – in fact, our team can speak in all major Indian languages. Besides, the time taken by Junglee to process users’ withdrawal requests is the shortest in the industry.

All of these factors keep our customers happy and lead to great customer retention.


NextBigWhat: How do you predict user behavior for new products/features? How is the product requirement process done, given that gaming is a very dynamic industry?

One of our values is that we obsess over numbers to drive decisions. This is ingrained in our company culture. The data that we have on user behavior, churn rate, how a user moves through an acquisition or retention funnel is then discussed by the various stakeholders, and a requirement is raised for a feature request.

The industry as a whole will move toward behavioral analytics in some time, and we want to get a head start. 

Also, as a process, we dive deep into all the issues raised by our Customer Success team, and when we find a pattern in the issues, we roll out a feature to solve the problem. Gaming is driving innovation across all domains, be it engineering or marketing automation or new user on-boarding, but sometimes a feature can come from learning something from another, completely different industry.

It always helps to keep your mind open.

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AI in Pathology: How this startup aims to detect cancer at your local clinic #AIBOSS

We, at NextBigWhat, are attempting to drive forward the conversation around Artificial Intelligence in India beyond headlines that scream for attention but don’t offer much, buzzwords that make your head buzz after a while, and countless utopian tales that vie for your eyes only to leave you with a scratching head and a lingering itch to actually get to the meat of the matter.

In this spirit, the #AIBoss series intends to educate, inform and elevate our readers understanding of the subject as well as the space. If you’re part of the leadership team of an AI based product, from enterprise or startup, willing to share your AI learnings – then reach out to us and become part of this initiative (you can apply using this form).


adarsh-aindra
Adarsh Natarajan, CEO & Founder, Aindra alongside the company’s computational pathology devices.

Adarsh Natarajan is the CEO & Founder of Aindra, a medtech company that offers AI based computational pathology solutions. Their first product, CervAstra, is aimed at automating the detection of cervical cancer, an illness which causes more deaths in India than in any other nation. Aindra says that their core computational pathology platform, Astra, has been designed to be extended to various other critical illnesses including, but not limited to, other types of cancers.

We caught up with Adarsh for a comprehensive tête-à-tête about Aindra, the kind of work they’re doing, how AI can help solve healthcare woes in India, the challenges that exist in AI diagnostics, and much more.

How would you introduce Aindra?

So, to put it a little technically, we are an AI-based computational pathology company which we leverage to provide point-of-care diagnosis for critical illnesses. In layman terms, we provide the ability to detect certain kinds of cancers right at ordinary physician’s clinics.

So, from scanning the history of Aindra, it seems that you pivoted from education-centric AI solutions to AI Diagnostics. So how did you arrive at the decision and what prompted the change?

Initially in the AI space we were looking at completely different use cases. We were going to do identity management in the education space, and then we pivoted away from the education space and started doing stuff for other sectors with broader positioning. We started looking at computer vision much more broadly – not just face recognition, which we started with – and I had a moment where I realized that it has tremendous application areas.

Technology like AI and Computer Vision have vast, multiple application areas. That’s when I started meeting people from across sectors and domains to talk to them and understand what is happening in their spaces. I met people from the automobile industry, manufacturing, textiles, and then also in healthcare – and healthcare struck a chord with me.

There were much more lucrative and easier routes in other segments, but what struck me was that we could democratize technologies like this and make it available for a large population to solve big problems in an economically viable manner. I felt passionate about that.

And so, we zeroed in on cervical cancer as the first condition to take on, while realizing simultaneously, that this would probably be our first beachhead and that the core technology would be leveraged to tackle other conditions going forward.

ai-healthcare

What were the initial challenges you encountered when you began building a solution for the clinical pathology space?

I come from a technology background, and we started with building only the AI software part as proof-of-concept and tried it out on small data sets. But there were absolutely no enabling systems available which would help the AI…

You mean integration to facilitate the transfer of data from slides to the system?

Yes, but there weren’t even any systems to capture the data first. You need to capture it, then convert it into a digital format and then apply the AI algorithms. So we built the AI algorithms and were quite gung-ho about it and then when we started talking to customers we realized that we hadn’t done a good job in assessing the limitations.

We wanted to provide the ability to detect critical cancer conditions not only in tertiary care oncology centers in cities like Bangalore, Mumbai, Chennai and Delhi but also make it available to primary physicians or clinics in faraway Tumkur, Bijapur, Ballari – tier three towns.

If that were to happen, we had to build the enabling systems too and backwards integrate them to create an end-to-end ecosystem. That meant building hardware which just wasn’t available commonly. The bitter truth hit home that India still imports 75-80 percent of its medical devices from outside and most aren’t built for point-of-care but for centralized large centers such as a Vedanta or a Fortis. So, we had to design everything from the ground up to take the bull by the horns in this space and truly create a point-of-care system.

pathology-ai

To build the ecosystem of the product, so to speak…

Yes. What started as one bespoke application morphed into a solution with multiple components all working in tandem to act as a single end-to-end product. Which meant we had to deal with designing hardware and getting them into manufacturing them and sending them into queue, so it is a whole different ball game than what we had expected.

Tell me a little about the deep learning systems you’ve implemented.

When we started off, deep learning was quite nascent in terms of its maturity, so we began with traditional machine learning techniques. We then started experimenting with deep learning because it has given us a quantum leap over some of the traditional techniques. But even today, it’s not one size fits all. We’ve really had to tinker, experiment and build a suite of algorithms to make it work. Today, we have a mix of deep learning and traditional machine learning to do the processing and then newer techniques like Deep Neural Networks, which brings its own strengths.

We also have to deal with the hard constraint of being in the medical world, where data is a real luxury. It’s not like we’re dealing with consumer data where you can crawl the web and scrape endless amounts of information to feed into your system.

So we’ve used some standard frameworks like TensorFlow and Caffe. We’ve also had to use transfer learning because of the insufficiency of data as I mentioned earlier, and build customized networks to deal with it.

adarsh-aindra2

On the clinical side, how did you go about partnerships and sourcing the data?

We had to partner with a very reputed tertiary oncology center called Kidwai, which is one of India’s best, go through an extremely long cycle of approvals before we got the final go-ahead. We then worked with their pathologists and used data from their archives. So we basically co-opted them into co-creating the product and the algorithm. They imparted their clinical expertise and we translated it into an effective AI. It was a long journey beginning with extracting medical data, drawing useful information from it and so on. Digitization of the data was a big and crucial part i.e turning archived glass slides into usable data format for training our system. We are now in the stage of clinically validating many of our solutions which will be done by mid-2019, hopefully.

And I’m guessing all of this data ultimately feeds to your computational pathology platform named Astra. What can you tell us about it?

With the computational pathology platform, what it allows us to do is extend our application area to tackle other conditions by retraining newer models with newer data by leveraging the same layer flow framework. We’ve been looking at other cancers such as blood cancers, leukemias and hope to move from cytology to even histopathology – which is the study of tissues – which means we would be going after prostate cancers and the like.

pathologist-in-lab

I was just about to ask you if Astra could potentially tackle detection of organ malignancies and other forms of cancers…

Yeah. I hope that answers your question somewhat. We’ve taken a lot of pain and effort to get to where we are today. And in hindsight, it was worth it because it has now prepared us to replicate it in an easier manner since our learning models can be fed with newer data to provide effective results. As an experiment, we’ve been able to prove this to ourselves by using a completely different dataset that deals with breast cancer tissue and we achieved equally good results as our core solution that deals with cervical cancer. Which means our network is now generalizing well enough.

What are the current challenges in cervical cancer detection? You mention affordability as being one on your site, but in my conversations with a few pathologists I was told that it is per se not a major problem.

There are multiple levels of efficiency and it’s not just one aspect that counts. When we talk about the cost of a test, it’s not just the price of a pap smear test that a woman has to deal with.

Imagine you had to get some kind of a test done but it is only available in Mumbai, it costs a 100 Rupees but you’re in Bangalore. The cost now increases exponentially because you have to spend money on travel, take a few days off from work and so on. For women in India, it could mean having to leave children and family. And if you’re a daily wage earner, then it would mean having to lose your paycheck for a few days. So it all adds up. If the test was available to you closer to where you live or work it would make a major difference. Accessibility to proper mechanisms drives affordability.

Let me give you an anecdotal reference, I have seen with my own eyes a pap smear test report (along with the bill) costing 2000 Rupees at a panchayat away from Tumkur. The same test in Bangalore would cost you 500-1000 Rupees. If you’re a below poverty line patient, and you go to a center like Kidwai, it would probably cost you 200 Rupees.

So you can see how the problem gets acute in an inverted way. Ultimately, the pathologist who actually who is doing the reporting is probably going to be paid the same amount. The center which picks up the sample had to handle logistics to transport it to Bangalore, there is labor involved in a clinic, margins involved and so on. The cost ultimately gets padded up.

robot-ai-medicine-health

So that’s the economics of the problem. What are the other challenges?

Awareness is a major challenge. And that is compounded. How many of us actually go for regular health check ups once a year? Very few. We don’t go to a doctor unless we’re sick for sure or feel a lot of pain. Or if your employer has a corporate healthcare plan so you get preventive health check ups. Or perhaps your insurance provider compels you to get them done. These are some of the triggers. Now imagine you didn’t have these triggers and you had to travel the distance of Bangalore-Bombay for some basic diagnostic tests. That would worsen your willingness.

Factors such as this compound the problem and have led to India becoming the cervical cancer capital of the world. One woman dies every seven minutes due to cervical cancer in India. These are official numbers. And we’ve been talking for longer than that, so you can do the numbers.

Remember, too, that many people who die in India never actually get the right reasons ascribed to their deaths at all.

Your solution then also provides advantages in terms of turnaround time for cervical cancer detection, obviously…

Currently, if you’re in certain tier-II cities or towns that border them, the turnaround time is around 4-6 weeks. The analysis itself doesn’t take that long, but because it has to be picked up and transported to, say, a Kidwai or St. John’s, who are already having to deal with their internal requirement, and then get entered into their backlog.

With a point of care system like ours, the patient comes in, provides the sample and within an hour and a half, during which she could get other tests done, she will have her report ready. This fundamentally disrupts a lot of things.

cell-microscope

One of your stated aims is to democratize access to healthcare and this certainly seems to fit the bill…

Yeah. Pap smear testing is not something that we have invented. It’s a proven technique that is well tested and has existed for decades. With proper testing and proper usage, cervical cancer rates can dramatically come down as evidenced by the incidence and mortality rates in the US and UK, where screening or yearly or at least bi-yearly tests are done on a very regular basis.

In India, with the population, lack of accessibility, and heavily negatively skewed physician to patient ratio, you’re never going to be able to fix it unless technology acts as a force multiplier. And I’m not just talking about this particular condition, any condition for that matter.

The US has 23 doctors for every ten thousand people and the UK has about 25. India has 7. So this is a systemic constraint.

And you certainly cannot manufacture clinicians overnight either…

Absolutely. Let’s take cervical cancer, for example, which, in India, has around 350 million women in the risk category. Which is more or less the size of the population of the United States. How can we possibly change the status quo dealing with this kind of scale if we keep doing the same old things expecting new outcomes?

The primary health centers which you’re keen to provide your solution to have their own challenges. Such as lack of electricity, non-availability of round the clock internet and so on. Have you factored those in?

Absolutely. Which is why we don’t have the AI algorithms on the cloud. We haven’t built an exotic or esoteric application with the assumption that there’ll be connectivity around the clock or that there will be electricity round the clock.

This is an edge computing device, where the first level of triaging – whether a sample is normal or abnormal – takes place in real-time. For confirmation, we bring in a pathologist for a report on a non-realtime basis. So once the sample is analyzed by a pathologist, only then is the confirmation provided.

What we’re doing is decoupling the need to have a pathologist available all the time for analysis and reporting. From a medico-legal perspective, we still have a pathologist sign off.

pathology-ai

It’s timely you say that. Because one of the questions I had was whether your solutions are built into the hardware, cloud-based or some kind of a hybrid model…

Yeah. Putting it on a edge device is extremely hard because you’re talking about algorithms which require serious computing power. The easy way would have been to put the solution on the cloud, where it would only work in urban centers with good connectivity but that would not serve the purpose at all. So we really had to re-look at every bit in the entire value chain to decide what had to be done.

Are primary health centers the only place where this could be disruptive?

We’re not just talking about primary care centers, we’re also looking at gynecology clinics who don’t do cervical cancer testing because they don’t have the equipment or the resources to do it. They will just refer the patient, if at all, to a pathology lab which itself has a host of problems as I mentioned earlier.

So, imagine a patient walks into a gynecology clinic and the gynecologist has two compact devices on her desktop. The gynecologist collects the sample, does the examination and in a short while the system confirms whether the patient needs further scrutiny or can be sent home. It could be that simplified.

What are the challenges you’ve faced in implementing the AI on your custom hardware?

We had to keep in mind the kind of computing power necessary and figure out the kind of GPUs we need and whether they’re available in the form factor that we desire. Our goal was to put out a model with a smaller footprint device. We had to also optimize how and at what speed the data is processed based on computing ability. And so on. A lot of thought went into it.

aindra-screen

Pathologists I spoke with told me that some of the legacy machines throw up red flags in case of ambiguity in data interpretation, which meant that they would have to manually confirm some of the findings. What kind of manual fallbacks have you incorporated?

As I said earlier, at the first level we do a triage result – normal or abnormal – and we indicate areas of abnormality. We present the findings to our panel of pathologists via our telepathology medium and once they sign off, the report is sent back. The findings of our system are presented to the pathologists, as they analyze, to assist them by calling out the areas where it has detected abnormalities, speeding up the process.

I was told that there might be situations where further data is necessitated from the primary clinician…

Clinical information such as the age of the woman, whether she is married or not, or how many kids she has, whether she has had multiple partners, whether she is menstruating or not etc. is already collected without us being in the picture. This is done by the primary care physician and this data, too, is presented to the pathologist if the system finds any abnormalities. And they can choose to override the system if need be.

A number of industries have seen transformation due to the revolution of low cost sensors. Have you benefited from it?

Absolutely. A lot of things we are able to do is because of convergence of a lot of these factors which have driven down the cost of computing dramatically. If that wasn’t the case, we wouldn’t have been able to make use of our technology. And sensors too, which are crucial to our solution. Advances like these have played a large part in democratizing technology. Which is why I believe we’re in a great point in time. If only India had a semiconductor industry, we could’ve achieved enormously. But it’s an imperfect world.

Broadly, what is the response to AI Diagnostics in India?

There’s a lot of apprehension as well as interest right now, depending on who you talk to. You’ll largely find a bit of both. Some people are threatened with the advent of technology and there are a few people who are able to look at trends that are unfolding and much more accepting of the changes. There is certainly a high level of awareness about the oncoming of AI.

What is the biggest challenge in your view in diagnostics/medical AI?

From my experience of having spoken to various researchers, academicians and clinicians, the biggest challenge globally is integrity of data. That is super critical for AI to become a widespread reality. Since we’re all going to be relying on large amounts of data to make our models as effective as possible, we have to ensure high integrity of data. This means ensuring minimal bias in data because biased data in medical AI is turning out to be a massive problem. Sadly many AI companies aren’t even aware of how important this is – it could determine the success or failure of their systems.

(Special thanks to Dr. Neha Ratan B, M.D. Pathology for her inputs.)

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“95% of the decisions that a consumer actually makes is subconscious.” #AIBoss [Interview With Ranjan Kumar, Entropik]

We, at NextBigWhat, are attempting to drive forward the conversation around Artificial Intelligence in India beyond headlines that scream for attention but don’t offer much, buzzwords that make your head buzz after a while, and countless utopian tales that vie for your eyes only to leave you with a scratching head and a lingering itch to actually get to the meat of the matter.

In this spirit, the #AIBoss series intends to educate, inform and elevate our readers understanding of the subject as well as the space. If you’re part of the leadership team of an AI based product, from enterprise or startup, willing to share your AI learnings – then reach out to us and become part of this initiative (you can apply using this form).

Here is our interview with Ranjan Kumar, the founder & CEO of Entropik, a company that specializes in ‘Emotion AI’ – a suite of technologies that allow brands and creatives to truly guage the emotional response of consumers with the incorporation of brainwave mapping, facial coding & eye tracking.

NextBigWhat caught up with him for an extensive discussion on Entropik’s product, the ethics of emotion tracking technology, where AI is headed and how their proprietary technologies are making an impact in various business verticals.

How would you describe Entropik?

At Entropik we work in the space of emotion intelligence. So what we do is basically, track consumer emotion at its point of origin in a scalable way. We’ve built technologies around brainwave mapping, analyzing facial expressions, analyizing eye tracking, so these are the fundamental proprietary technologies which actually allow us to decipher the subconscious aspect of human behaviour. And 95% of the decisions that a consumer actually makes is subconscious, however most of the analytics aligns around the conscious aspect of user behaviour. So we’re taking our shot at tracking the subconscious aspect of human behaviour.

What are the current and upcoming applications for your product suite?

Right now we’re very focused on media experience testing. So anything video – right from ads to trailers to long-format TV shows and even 3-hour films. Where you get to see on a second-by-second level what the emotional response of the user is, be it happy, sad, excited or bored. In addition to that, we also track what the attention level is, where the mental engagement stands, and quickly you can get to know the parts of the video that least engage the viewers.

UX testing is another area where we offer great value. Some other areas are chatbot experience testing and shopper experience testing. So while you’re walking in the store, we can track where you’re looking and what sort of brainwaves are being generated. Whether you’re attentive and feeling excited or bored etc.

Edtech too is emerging as a big market. We’re using the technology to validate psychometrically the cognitive learning index of a student. Retail is at an early stage and automotive is an upcoming market where companies want to track fatigue and stress levels of drivers.

What was the pain point you set out to solve specifically with Entropik in its early stage?

One of the resons why products fail is because they don’t resonate with consumers. Every consumer brand, the biggest pain point or the fundamental question is whether I can decipher what the consumers are feeling, what their preferences are, and hence align and create a product which is likely to resonate at a more cognitive level with the user. The first step to that problem is knowing whether you understand your consumer very well and whether you understand not just the conscious aspect of their expression, but also subconscious behavior and subconscious elements which tie into the buying pattern.

We looked at what makes a purchase decision or what makes a content consumption decision: fundamentally 95 percent of your decisions are subconscious. That means we need to have analytics to pick up on this aspect of consumer preference. So that’s a huge problem.

Look at the kind of losses companies have when they actually roll out a product and it fails. Or if a movie is released and it fails – we’re talking about huge losses. Efficiency of success of product content is around 2 percent today. So we set out to solve this 98% inefficiency problem.

Based on the sweep that you have in terms of what you could do with this kind of technology on scale, could we be heading towards a Huxlian world where everyone’s emotions are fine tuned to an inch of what is being intended to evoke – pleasure, sadness and so on?

I don’t think that will happen. So, you have AI which is about intelligence i.e it is logically intelligent. It has a bunch of ‘if x’ rules, that is ‘if x then do y’. A huge collection of such rules is called artificial intelligence. What it lacks is empathy and emotional intelligence, which means that it is answering a question but without the context of my current emotion.

When two people are interacting, emotion is a factor which makes human communication unique. That aspect is missing with machines. So I think that brings a lot of resonance but I don’t think technology will be modifying people’s behaviour in the way that you envision. I think it is solving a gap of 98% inefficiency of interaction between man and machine. That’s about it.

When it comes to ads, there is an explicitly commercial element to it therefore optimizing for it in the manner that Entropik allows makes sense to a great degree. With movies or TV shows, however, what if production houses begin to edit films based on the responses they see on a system, rather than it being the relatively untramelled creative vision of a director – how do you see that playing out?

That’s something we face day in and day out. We currently work with almost every major broadcaster in the country. And we’ve faced this question before. What our product can do is two things: a. It can help marketeers optimize how they reach customers. Help improve business outcomes. b. It helps creative guys to optimize on the content itself. We’ve been very cautious not to step on the toes of those in charge because the relationship should not trample on their creative vision. We look at ourselves as enablers.

For example, if we’re recommending that these are the 10 things that came out of analyzing this piece of content, then they mostly agree or disagree but still do what they have to do. So that freedom is never taken off from them. And we’re receiving a lot of intelligence from their end as well and we need to make sure that we’re incorporating that into our system. So as to make it even more intelligent. And the other important thing is that most of these studios are sitting on hundreds of scripts, and they require a system that can evaluate these ideas in the quickest way possible – which is where we come in as enablers.

You can watch the full interview in the embed above. Make sure to subscribe to our Youtube channel for more such engaging videos!

“We have never looked at automation as a way only to cut down on cost.” #AIBoss [Interview With Parag Arora, Glowing.io]

We, at NextBigWhat, are attempting to drive forward the conversation around Artificial Intelligence in India beyond headlines that scream for attention but don’t offer much, buzzwords that make your head buzz after a while, and countless utopian tales that vie for your eyes only to leave you with a scratching head and a lingering itch to actually get to the meat of the matter.

In this spirit, the #AIBoss series intends to educate, inform and elevate our readers understanding of the subject as well as the space. If you’re part of the leadership team of an AI based product, from enterprise or startup, willing to share your AI learnings – then reach out to us and become part of this initiative (you can apply using this form).

Here is the second and final part of our interview with Parag Arora, who is a technology entrepreneur with deep insight into messaging solutions, having sold his first startup Plustxt to Paytm in 2013 and currently holding the position of Chief Technology Officer at Glowing.io – a YCombinator selected startup that provides an AI based messaging solution to the hospitality industry.

NextBigWhat caught up with him for a rather extensive tête-à-tête on the journey of Glowing.io from conception to product, AI & NLP in the hospitality space, and whether or not he considers voice based solutions like Alexa a threat in the coming future.

In terms of the tech stack, how does Glowing.io operate? How has it evolved over the product’s lifetime?

The heart of the messaging system is Erlang based RabbitMQ and we have evolved from XMPP based architecture which was also used in Plustxt, later sold to Paytm.

Glowing.io posed new challenges for providing enterprise-grade features as assignment and removal of conversations in real-time manually by staff or automated by our system.

Apart from this, the business layer is built over Ruby on Rails with backend as PostgreSQL. We use native apps for mobile and nodeJS for our messaging infrastructure. For the frontend we use ReactJS.

Two main infrastructures we have developed over time are QA and DevOps automation. We are currently deployed over AWS and Alibaba and both have proved to be very crucial components for us over time.

messaging

What kind of machine learning systems has Glowing.io implemented and what do you hope to achieve with it?

Our main focus has been on NLP and further automating tasks inside the organization achieving operational efficiency as an end goal depending on integrations we have done with other systems of that particular hotel.

What are the kinds of analytics you use to measure guest success on the hotel end – as in, what kind of analytics do you make available to them – as well as customer success on your end i.e the KPIs you use internally?

We have a customized analytics dashboard inside the product and the most important component we currently focus on for customer success is guest engagement – which is essentially a percentage of new guest conversations compared to new guest check-ins on a particular date.

With the onset of Alexa and other voice based solutions which are seemingly being adopted in the hospitality industry, do you view them as a threat or as something that you can integrate into your solution? Or even, perhaps, build on top of it?

For us, Alexa is just like any new communication channel. We aim to be the digital hub for hotels for guest conversations.

The only difference we see is that guests are already trained to receive automated instant replies to Alexa compared to messaging channels where guests expect human-like conversations.

messaging

Since a product like Glowing.io would presumably entail deep integration into a hotel’s processes – what is the flow like in terms of training hotel staff/personnel to get to grips with the solution? And what kind of timeline do you maintain for it?

We understand introducing a new system with a new process takes time and we give hotels enough time to internally align. Although the overall onboarding can be done in a day, we have divided the onboarding in 45 days with weekly sync-ups to ensure the program is successful from operations, marketing, branding, and sales side.  We also provide an optional onsite training program which I personally love a lot as we get to learn a lot about the property and it provides an opportunity to travel to beautiful places and experience their hospitality.

Developing markets have the advantage of cheap labour – is it a safe assumption that they would rather have a human behind the screen than invest in an AI? And have you come face-to-face with this in terms of sales across geographies? How are you dealing with it?

Interestingly Glowing.io is deployed in equal proportions in developing economies as well as developed. We have never looked at automation as a way only to cut down on cost and resources but rather as a way to be operationally efficient, correct and more data-driven.

According to you, what is the future of conversation between customers and companies in the context of chat, voice and more?

I think the future is that humans will be for emotions and AI will be for automation, taking away the pain and time of redundant tasks. I see a beautiful world of happy employees in hospitality and AI-enabled hospitality for brands who have hospitality in their DNA.

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“Communication data itself is extremely important for hotels which was not being captured until now.” #AIBoss [Interview]

We, at NextBigWhat, are attempting to drive forward the conversation around Artificial Intelligence in India beyond headlines that scream for attention but don’t offer much, buzzwords that make your head buzz after a while, and countless utopian tales that vie for your eyes only to leave you with a scratching head and a lingering itch to actually get to the meat of the matter.

In this spirit, the #AIBoss series intends to educate, inform and elevate our readers understanding of the subject as well as the space. If you’re part of the leadership team of an AI based product, from enterprise or startup, willing to share your AI learnings – then reach out to us and become part of this initiative (you can apply using this form).

Here is the first of two parts of our interview with Parag Arora, who is a technology entrepreneur with deep insight into messaging solutions, having sold his first startup Plustxt to Paytm in 2013 and currently holding the position of Chief Technology Officer at Glowing.io – a YCombinator selected startup that provides an AI based messaging solution to the hospitality industry.

NextBigWhat caught up with him for a rather extensive tête-à-tête on the journey of Glowing.io from conception to product, AI & NLP in the hospitality space, and whether or not he considers voice based solutions like Alexa a threat in the coming future.

For those who’re unaware, how would you describe Glowing.io?

Glowing enables digital communication between hotels and guests with the main focus being on enhancing guest experience while at the same time increasing the operational efficiency of hotels.

How did you arrive at the pain point and then eventually the product?

For me, it was a mix of personal experience and excitement when I saw immense opportunities for implementing technologies I love and have built at previous companies.

On the personal side, I always felt a gap when visiting even luxury hotels where I was not able to enjoy basic experiences like ordering a beer without physically having to move when chilling near the swimming pool and so on.

I personally see it as a big trend now that people prefer buying international internet packs than voice packs which creates a problem when you have to connect with your hotel. Also, in extremely busy schedules – people always prefer texting more than having to wait to talk to the hotel over voice calls.

On the technology side the opportunity is huge, as guests are going to connect to their hotels pre-stay, during stay and post stay and the fact that the problem of broken communication can be solved to the extent that conversations can be 100% automated eventually is pretty exciting.

This communication data itself is extremely important for hotels which was not being captured until now and a lot of interesting things can be done over this data.

Product conception was done mainly to solve the problem of digital communication at hotels as a first step with the realisation that we need to fix other problems which this means affords us to solve, such as communication barriers owing to factors like language, reluctance to talk, downloading a new application from guest app etc.

Also, the ability for hotels to have centralized data of messages where conversations can be assigned and escalated.

What was the process like in terms of evangelising hotels to adopt the service?

There was definitely a gap between hotels’ understanding and guest needs initially where hotels used to believe conventional face-to-face is the mechanism of communication guest prefer.

Two major things which have changed that perspective is the rise of the millennial market for luxury travel and international travel with a lot of communication barriers.

We believe the ability for guests to communicate in their own language over the messaging platform they are already used to, in their interaction with their friends and families, is going to redefine the relationship between hotels and guests.

Most of the evangelism process was involved in educating hotels on the benefits of messaging by showcasing how seamlessly they can provide guest services once they integrate all their systems to the communication platform itself (Imagine guest orders food over WeChat in Chinese in Switzerland and ticket is automatically created in Food Ordering System).

What are the frictions in the hospitality industry that Glowing.io went in to solve and what were newer ones you were able to learn from your customers?

There were mainly two kinds of frictions we have faced from the industry, one was the reluctance of hotels as they started believing they will need to add more resources for communication and other was the reluctance of staff in trying a new product.

Providing demo and onboarding to staff became a winning factor to solve the above problems where we designed the system to minimize decision making and in using the product. The most important thing was we had started selling and talking to hotels before even building the product and we were well aware of these problems which also formed as a core design philosophy behind while building Glowing.io.

On onboarding, we worked with a general manager of one of the most luxurious properties of the world who helped us create the complete onboarding program for Glowing which also we have automated a lot during our journey with help of quick videos and inside the product.

There seems to be some confusion with regards to the level of overlap between AI & NLP – there are some who question whether NLP integration can be legitimately claimed as a significant AI-based feature when today companies and startups are simply plugging into pre-existing libraries. How do you look at this and could you help clear the confusion?

AI is a field of computer science which was created mainly to solve tasks easier for humans but hard for computers. With new advances, AI is matured enough that we are able to solve problems that are hard for humans now but easier for computers. The eventual goal of replicating humans is much further away but definitely, new advances are approaching that direction.

NLP is just a part of AI focused on solving problems around languages.

There are a lot of plug-and-play solutions available in the market which are very cost effective as compared to building our own systems. The answer we need to find is what to do with these tools.

It is more like deciding whether to go for cloud or to host your own servers. For businesses I always advise to go for tools if they are mature enough and solve your needs. Most of these tools also provide probabilistic confidence on the solution where UX plays an important role in improving via feeding back data combined with human assistance.

Only drawbacks are with tools which do not provide a functionality to provide learning with data.

Our experience with NLP is for texting in international messaging where messages are well formatted and are not very long and for these kinds of messages, NLP out of open tools such as Google works amazingly well.

There are a lot of advances still needed in NLP which could thread sentences from the context as currently NLP tools provide line by line translations without it.

In short, NLP definitely is part of AI strategy and companies are making decisions not just in NLP just as plug-and-play but also in a lot of other contexts for AI and that is the best move until you find that no external tool will answer your need or have concerns on data privacy (e.g. in GDPR).

Since Glowing.io is described as a ‘bot and human-assisted AI’ platform – in which hotel processes is there a bot enabled and where does human intervention come in? And what was the research process like in going about designing it?

I cannot name hotels who are currently automating conversations for various reasons. Human-assisted is a rule-based algorithm which mainly comes in when there are discussions happening on mission-critical tasks like reservations or when probabilistic confidence is lower than a certain percentage for understanding context or a reply of that particular context is not handled by the bot.

A good example of where the bot is used  is during checkout. As it’s extremely important for hotels to know someone is checking out since they can schedule cleaning and upsell room for early check-ins but guests generally don’t want to go through the hassle of formally checking out.

There are other instances where guests ask questions like ‘where is the buffet’ etc. Most of the usage of bots are in what we call “goal-based conversations” where the discussion is not open-ended but the guest has a specific task in mind or wants to know a definitive piece of information.

Research process involved taking into account a lot of first-hand experience in understanding conversations happening over Glowing as well as visiting properties and finding out how requests are taken care of in terms of operations. A lot of focus while automating conversations is always given for operational efficiency in achieving tasks.

Since Glowing.io supports interactions in multiple languages, have you also implemented NLP for non-English languages and what challenges did you face in the process?

We have not implemented NLP in non-English languages natively and therefore translate and then attempt to understand the context. It is harder to scale NLP to other languages as models and the whole system becomes drastically different and each language looks like an opportunity to create a huge organization. This is still a problem which needs to be solved and most solutions right now focus on keywords based approach.

The second part to this interview will be published tomorrow. Make sure you’re subscribed to the AI Boss newsletter to keep up with the latest in AI developments across the world!

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“Agriculture tech will revolutionise this country more than ecommerce ever did.” #AIBoss [Interview With Shailendra Tiwari, Fasal]

We, at NextBigWhat, are attempting to drive forward the conversation around Artificial Intelligence in India beyond headlines that scream for attention but don’t offer much, buzzwords that make your head buzz after a while, and countless utopian tales that vie for your eyes only to leave you with a scratching head and a lingering itch to actually get to the meat of the matter.

In this spirit, the #AIBoss series intends to educate, inform and elevate our readers understanding of the subject as well as the space. If you’re part of the leadership team of an AI based product, from enterprise or startup, willing to share your AI learnings – then reach out to us and become part of this initiative (you can apply using this form).

Here is the third and final part of our three part interview (Part I, Part II) with Shailendra Tiwari, founder of Fasal, an Ag-tech (agriculture tech) startup that is focused on building AI and IOT (Internet-of-things) based SAAS solutions to address the woes of Indian horticulture farmers. Fasal’s primary aims are to increase and improve the quality of the yield and lower input costs for the farmer. It is currently deployed in farms across Karnataka, Maharashtra and Chattisgarh.

In this interview, Shailendra gives us an inside view of agricultural tech in India, how Fasal is seeking to disrupt the space and why agri-tech stagnating has more than just a little to do with it involving the sweltering heat in Karimnagar as opposed to the air-conditioned cabins in Koramangala.

Q14. Are you looking at drone integration going forward considering it is being utilized by high-end farms in some regions of the world to disperse water and/or pesticide?

Yes we are. In fact the way Fasal has been architected is to make sure that we can collect data from any source. Be it sensors, satellites or drones.

And let me tell you, not only in Hi-tech farms, I have met farmers with 3-4 acres of land exploring drone solutions.

Don’t forget finding farm labourers is becoming a big and visible problem now. If we can provide drone services at a cost equal to that incurred with that of labours, I don’t see a problem in their larger adoption if these solutions can reach out to the farmers in need.

Q15. It would be safe to assume that apart from key fundamentals, each crop needs its own software and system. What is the research process like and could you share some interesting learnings from that?

Wonderful question. I assure you that each crop/each region has its own requirements. For example there are regions in India where a disease called Powdery Mildew is a big big problem for chilli. But for the same chilli, in a different region, it is practically non-existent.

For us, even deciding which is the next crop we should go after, is complex decision involving agronomy, farmer personas, regions where it is grown, financial consideration, cost of cultivation and at least 10-15 more considerations.

Once we have decided which crop we pick, we do a thorough research on it’s lifecycle, the pests and disease which are a menace to it, the irrigation patterns and practices followed, the amount of research done on that crop across the world, the amount of research done on that crop in India. Post that we identify the biggest problems farmers face with that crop. Once that is done, we do a technical and domain assessment of the feasibility of building solutions around those problems. Once all of this is done, then starts the process of research and development on building and validating the needed solutions.

Q16. Legacy agricultural research institutes have been around in India since the British era and a lot of research work is conducted in India today too – have you been able to take advantage of both the organizations and the corpus of material and/or is there any kind of institutional partnership you’re contemplating in this field? Considering you’re well placed to translate that traditional research into tech solutions.

I absolutely love how this question is framed. These are the same words in the same order I have used at certain places. In fact I was at University of Agriculture sciences, Bengaluru recently and Dr. Chandrashekara, head of entomology department and I discussed this at length.

There is good research in the universities of India. We have very learned agri scientists and professors in India. And as startups we do have the opportunity to take the research done to where it belongs, the hands of farmers.

We at Fasal have been doing it and will continue to do so extensively in future. In fact through this answer I invite any university/scientist/professor who wants to collaborate with Fasal. Not only this, we have also been working on partnering with universities/institutions for the greater good of farmers very very actively.

Q17. Tell us about your tech and AI stack.

Said much already 🙂

Your readers may need to sign an NDA to know more (pun-intended) 🙂

Q18. What can you share with regards to your emphasis on sustainable farming?

To be honest, there is no option but for farming to be sustainable. If we continue with current ways, we will reach a point of no-return. We have to bring awareness that everytime a farmer sprays an extra dose of pesticide on the farm, what ecological damage happens. We have to bring awareness that everytime a farmer irrigates for an hour more than needed, what the world loses and much much more.

I imagine the scenes from Christopher Nolan’s movie Interstellar where Blight has taken over the world and food production is under severe threat and thus humanity’s survival. It may sound far-fetched but if you start analysing the current scenarios on scale, you may realise that it may not seem so far fetched as it does.

Q19. Globally and in India, where is agri-tech and where do you see it heading?

I say this to everyone who puts up a similar question. Keep a track of Agtech for next 4-5 years.

A lot is going to change. Technology and solutions will revolutionise the way farming is done. We will move towards a more efficient and sustainable ways of farming. Farmers will grow better, sell better and we will eat better. We will see technology enabled, one acre profitable farm models (something I am obsessed with currently) through which a farmer family of 4-5 will be able to live a dignified life. Given that we in India have more than 50+ million people directly/indirectly, imagine the impact Agtech will make at scale. It will revolutionise this country more than ecommerce did or more than metro-mobility tech did.

In fact I am waiting for a day when Agtech will help move the needle of the GDP that comes from Agriculture. And trust me that day may not be very far.

Interview Parts: Part 1 // Part 2

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“There is much much more to agriculture and farmers than the startup ecosystem understands right now.” #AIBoss [Interview With Shailendra Tiwari, Fasal]

We, at NextBigWhat, are attempting to drive forward the conversation around Artificial Intelligence in India beyond headlines that scream for attention but don’t offer much, buzzwords that make your head buzz after a while, and countless utopian tales that vie for your eyes only to leave you with a scratching head and a lingering itch to actually get to the meat of the matter.

In this spirit, the #AIBoss series intends to educate, inform and elevate our readers understanding of the subject as well as the space. If you’re part of the leadership team of an AI based product, from enterprise or startup, willing to share your AI learnings – then reach out to us and become part of this initiative (you can apply using this form).

Here is the second part of our three part interview with Shailendra Tiwari, founder of Fasal, an Ag-tech (agriculture tech) startup that is focused on building AI and IOT (Internet-of-things) based SAAS solutions to address the woes of Indian horticulture farmers. Fasal’s primary aims are to increase and improve the quality of the yield and lower input costs for the farmer. It is currently deployed in farms across Karnataka, Maharashtra and Chattisgarh.

In this interview, Shailendra gives us an inside view of agricultural tech in India, how Fasal is seeking to disrupt the space and why agri-tech stagnating has more than just a little to do with it involving the sweltering heat in Karimnagar as opposed to the air-conditioned cabins in Koramangala.

Q8. Farmers are presumably risk-averse, so how do you conduct pilot programs?

This question lit me up. I wonder, a farmer who leaves his business (farming) to the mercy of gods (weather) knowing that it is highly uncertain is risk-averse? Think about it for a moment.

While we were doing our pilots early in 2018, we had to choose only 6-7 farms to run our experiments due to resource constraints but we had a list of about 80 odd farmers from a certain region who themselves keenly wanted that our pilots are conducted on their farms with little to no effort on outreach for the same.

Trust me there is much much more to agriculture and farmers than the startup ecosystem understands right now.

Q9. Why do you think agri-tech has stagnated in India for so long?

If I take a moment and think about it, I am not sure if AgTech has stagnated. Things were happening all through. They may have been slow though. If you research, you will find Agritech companies founded as early as in 2010. Although what may be true is that the ecosystem has become a lot more enabling now. The government’s policies are shaping the perception. There are incubators and accelerators helping out. Investors are interested and most importantly the farmers are a lot more interested. The technology to do something meaningful for Ag is now in place.

Also, Agtech is difficult. It does not happen in air-conditioned cabins of Koramangala but in hot summers of Karimnagar in Telangana 🙂
It is a lot of hard work, and thus naturally it may not be the most exciting vertical for a lot of entrepreneurs. It requires a bigger motivation than just ‘starting up’.

But we are an inspired generation and I strongly believe 10 years down the line, farming in India will be very done very differently than it is done currently. Startups will lead the way.

Keep a track of Agritech, you will see a lot many entrepreneurs plunging in to take up the challenge of improving the agriculture ecosystem.

You may find me very optimistic but AgTech may produce a unicorn sooner rather than later.

Q10. Which crops and regions within India are you focusing on right now?

We are currently focused on Grape, Pomegranate, Chilli, Capsicum, Tomato and Potato crops and are serving farmers and agri-institutions in Karnataka, Chattisgarh and Maharashtra.

Q11. Which crops do you think are ripe – pun intended – for major disruption via solutions like Fasal?

We believe horticulture in general has a lot of scope. It’s definitely challenging but it sure will bear lots of fruits (pun intended).

Q12. On the regulatory end, are there any challenges you’ve faced so far and do you foresee any?

Not yet. But data ownership is a general concern across the board and it will have its implications on Agtech as well from a policy perspective.

Q13. What have been your major learnings in ‘building for Bharat’ (to borrow a phrase from Ixigo’s CTO Rajnish Kumar)?

This is a great question.

Very soon in our journey we realised that solutions from the West cannot just be copied here in India. India has a specific set of problems.

For Agtech ‘meaningful frugality’ has to be at the very heart of the solutions that we build and the solutions which will scale up.

Interview Parts: Part 1 // Part 3

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“Indian farmers are not anti-tech.” #AIBoss [Interview With Shailendra Tiwari, Fasal]

We, at NextBigWhat, are attempting to drive forward the conversation around Artificial Intelligence in India beyond headlines that scream for attention but don’t offer much, buzzwords that make your head buzz after a while, and countless utopian tales that vie for your eyes only to leave you with a scratching head and a lingering itch to actually get to the meat of the matter.

In this spirit, the #AIBoss series intends to educate, inform and elevate our readers understanding of the subject as well as the space. If you’re part of the leadership team of an AI based product, from enterprise or startup, willing to share your AI learnings – then reach out to us and become part of this initiative (you can apply using this form).

Here is the first of our three part interview with Shailendra Tiwari, founder of Fasal, an Ag-tech (agriculture tech) startup that is focused on building AI and IOT (Internet-of-things) based SAAS solutions to address the woes of Indian horticulture farmers. Fasal’s primary aims are to increase and improve the quality of the yield and lower input costs for the farmer. It is currently deployed in farms across Karnataka, Maharashtra and Chattisgarh.

In this interview, Shailendra gives us an inside view of agricultural tech in India, how Fasal is seeking to disrupt the space and why agri-tech stagnating has more than just a little to do with it involving the sweltering heat in Karimnagar as opposed to the air-conditioned cabins in Koramangala.

fasal

Q1. How would you describe Fasal?

Fasal is an AI powered SaaS platform for horticulture to make farm level predictions for increasing yield, improving quality of the yield and optimising input cost.

Q2. How did you arrive at this solution and what were the primary pain points you set out to solve when you began?

It is a long story, but to cut it short, the identification of the pain points that we are trying to solve is a result of an extensive mix of primary and secondary research done over a significant period. The solution that we are building is a result of co-creation between some really wonderful farmer friends, Team Fasal and some very learned domain experts.

Q3. On the tech side, what were the early challenges you faced setting up the product?

Unavailability of data and poor telecom network challenges gave/still give us a hard time.

Q4. What obstacles do you face evangelizing to farmers? Were you able to crack any stereotypes of Indian farmers being anti-tech?

I find this question really interesting.

And let me take this question as an opportunity to break some stereotypes in the first place.

We are a horticulture (fruits, vegetable, plantation crop) focused product. Of the many layers of Indian farmers, you will find the horticulture farmers to be different in their thought process. They are not ‘anti-tech’.

The penetration of micro-irrigation systems (technology of drip irrigation/sprinkler irrigation) is significantly high in horticulture. These farmers frequently utilize Whatsapp for conducting their business and Facebook for learning through various agriculture groups.

You may find it hard to believe but there are Indian Facebook groups with lakhs of farmers where they discuss problems/technologies and solutions 24 x 7 x 365.

They use many agri-related apps, thanks to the data revolution. And they really are looking for technology to solve their pressing problems. Pests and diseases being another. Irrigation being one.

The biggest obstacle that we faced when we started was people did not trust the benefits that we said farmers could get from Fasal. This was also expected and we did have the strategy in place to drive adoption. And it did turn out really well for us, winning their trust one day at a time.

Q5. How much of Fasal is standardized and how much is made bespoke for each farm?

Fundamental belief and the underlying assumption of Fasal is that each farm, farmer and crop is different.

We are crop focused and thus we work on building an end-to-end solution for one crop at a time, that is from sowing to harvest. We assume that the varieties of the crops will be different, the types of soil are going to be different etc.

The way we define Fasal is we make ‘farm level’ predictions ‘by crop’. In our experience, building anything generalised may not work out. The people who know agriculture also known with certainty that agriculture is a local problem.

Q6. Tell us about the kinds of sensors utilized by Fasal’s system and the nature of the data captured?

We collect data through all the methods possible. Fasal essentially is a data collection and intelligence delivery platform. We are hardware agnostic. We currently collected farm level data for macro-climatic conditions like wind speed, wind direction, rainfall and air pressure. Micro-climatic parameters like temperature, humidity and leaf wetness. Solar parameters like photosynthetically active radiation and lux. Below-the-soil parameters like soil moisture, soil temperature, soil ec and pH etc and many more.

Q7. What can you tell us about the AI integration within Fasal?

In a world where Fasal has succeeded in entirety will be a world where farmers are proactively managing farm operations rather than reacting to damaging situations. It could be scenarios of pest and disease attack, crop water requirements and so on and so forth. Thus predictive analytics is at the very core of Fasal.

We are currently very focused on improving and building two kinds of ML algorithms:

Microclimatic forecasting: Forecasting the microclimatic conditions of a farm over the crop cycle to give our farmers an edge in making preventive farm level decisions.

Pest and disease forecasting: A difficult task at hand but I am happy with the progress we are making in telling our farmers way in advance that a pest or a disease may attack. As a result of this, they can manage them in 50% lesser cost as opposed to the current practises.

For example for Grapes, which is a crop of interest to us, we can predict Downy Mildew, a damaging disease with high certainty.

Interview Parts: Part 2 // Part 3

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“Voice is going to lead the next phase of growth for the industry.” #AIBoss [Interview With Aakrit Vaish, Haptik]

We, at NextBigWhat, are attempting to drive forward the conversation around Artificial Intelligence in India beyond headlines that scream for attention but don’t offer much, buzzwords that make your head buzz after a while, and countless utopian tales that vie for your eyes only to leave you with a scratching head and a lingering itch to actually get to the meat of the matter.

In this spirit, the #AIBoss series intends to educate, inform and elevate our readers understanding of the subject as well as the space. If you’re part of the leadership team of an AI based product, from enterprise or startup, willing to share your AI learnings – then reach out to us and become part of this initiative (you can apply using this form).

Here is the second of three parts of our interview with Aakrit Vaish (you can find the first part here, and the third part here), CEO & Co-Founder of conversational AI platform Haptik. Aakrit co-founded Haptik in 2013 as a unique mobile assistant platform before it transitioned into conversational AI and is now one of India’s foremost platforms in that space.

Q 8. A confluence of technological developments are now helping voice become a serious contender to text – how do you see this playing out and what is Haptik doing to ready itself for this?

As mentioned in the previous question, Voice is going to lead the next phase of growth for the industry and subsequently Haptik in general. It just intuitively makes sense, it’s easier and takes lesser time to speak a command than type it.

We’ve built out capabilities to build voice bots, and are first large implementation goes live next week actually. Stay tuned and watch this space 🙂

Q 9. NLP in the Indian language space on a tech-level appears to be still in the rudimentary stages. Is this impression correct? And if so, what are Haptik’s plans in terms of working with Indian languages within chatbots?

Yes, you are right when you say it’s still rudimentary in terms of technology. But that’s also because the problem is so hard to crack. Most Indian speech is a combination of multiple languages and not just one. The concept of “Hinglish” is unique to India and there is no set data set available for it.

75% of our R&D efforts are going only towards getting vernacular languages right. We are going to be spending a lot of time and investment here, and expect at least 5-10 live implementations across languages from us in 2019.

Q 10. How does Haptik intend to stand out in the increasingly crowded enterprise chatbot market?

Focus on few key things:

  1. Largest base of consumer data – The fact that we also have a direct to consumer product means that we get real conversational data from end users, which helps train the models continuously over time. This just continues making our systems better, and always ahead of any other competition that will depend on third parties for this.
  2. Dedicated use cases – We will only focus on end consumer engagement and not touch internal operation areas like HR, IT helpdesk, etc. For our focus use cases, we will build out products to solve end to end business problems which could go beyond the scope of simple chatbots.
  3. Types of clients – We have a set target customer segment that is very refined and precise. We will only go after those and not touch anything outside.
  4. One stop shop – Continue to build and have all capabilities in house, such that our customers don’t have to go anywhere else to solve their set of problems.

Q 11. The fledgling self-service chatbot space appears ready for take off. Is Haptik planning to launch a DIY platform? And where do you see the DIY offerings settling?

The DIY mobile app space never took off, so I have my doubts here for chatbots as well. We have no plans to have a DIY platform, though I do see there could be some niche plays here if done correctly. Smaller market and a bit of a distraction for us.

Q 12. Haptik has an AI trainer team that works on the bots – what does that training entail exactly? Could you elaborate on the process? And what kind of skills does a ‘trainer’ possess?

Yes, that is again one of our differentiators. Our AI trainers take a bunch of unorganized data sets from clients and turn them into bot workflows using Haptik tools. These data sets could be FAQ documents, training manuals, product catalogs, etc. The tool then has a number of features for them to make the conversion happen.

The skill set an AI trainer needs to have is analogous to a business analyst. They need to understand the problem the client is trying to solve, take the data, use a set of tools and accomplish the tasks.

Interview Parts: Part 1 Part 3

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“A chatbot is only as good as the data you provide it.” #AIBoss [Interview With Aakrit Vaish, Haptik]

We, at NextBigWhat, are attempting to drive forward the conversation around Artificial Intelligence in India beyond headlines that scream for attention but don’t offer much, buzzwords that make your head buzz after a while, and countless utopian tales that vie for your eyes only to leave you with a scratching head and a lingering itch to actually get to the meat of the matter.

In this spirit, the #AIBoss series intends to educate, inform and elevate our readers understanding of the subject as well as the space. If you’re part of the leadership team of an AI based product, from enterprise or startup, willing to share your AI learnings – then reach out to us and become part of this initiative (you can apply using this form).

Here is the first of three parts of our interview with Aakrit Vaish, CEO & Co-Founder of conversational AI platform Haptik. Aakrit co-founded Haptik in 2013 as a unique mobile assistant platform before it transitioned into conversational AI and is now one of India’s foremost platforms in that space.

Q 1. For those who’re unaware, could you give us a short intro to Haptik and its history?

Haptik is a conversational AI company, started in August 2013. Here is an exclusive peak into our journey, never shared before on any public platform 🙂

The Haptik Journey // Source: Aakrit Vaish

Q 2. With the future in mind, how much of your resources and energy are you devoting to the B2C Haptik platforms as opposed to the Enterprise platform and why?

Most of our energy is on the enterprise platform as that’s where we see the greater need today. Automating customer support for brands through chat has proven out to be an ROI positive business case, and there is a huge addressable market.

The B2C app continues to remain an important showcase product for us, but currently is on autopilot. We will pick that back up once we find a better distribution mechanism for it.

Q 3. What were the initial challenges you encountered when entering the enterprise chatbot space? What was the evangelising process like?

Yes, the biggest challenge was actually evangelism and education. All enterprises wanted chatbots, but had no idea what business problem they wanted to use them to solve. Most of my job even today is just thought leadership about what bots can do, and more importantly cannot do.

This also lead to other challenges such as price discovery, no one was aware what is the right price which caused sales cycles to be terribly long due to unnecessary negotiations.

Q 4. Working across sectors in the enterprise space, were there any unique obstacles Haptik encountered and overcame which helped elevate the platform as a whole?

Yes, definitely there is a lot to learn from each sector which can then be applied to the platform as a whole.

For example in e-commerce, people’s patience levels are lowest because the typical query is for order status. So we had to ensure the platform is optimized for speed even if the answers may not be 100% accurate. Whereas in the case of say healthcare, people care more about accuracy of information so the bot needed to be spot on, even if it took 2-3 seconds extra.

This meant that we had to create custom levers for each of these parameters that enterprises can move up and down. That makes the entire platform more customizable and flexible to use.

Q 5. From my experience, users tend to feel a higher level of frustration when a support request fails to resolve via a chatbot than with a human at the other end. What kind of premium do you place on mapping the unique customer flows of each enterprise customer & how do you go about it?

Every single chatbot built on the Haptik platform is 100% customized, and all of the customization is done by our in house professional services team. This is a strong call we took early on when getting into the business, which was unpopular with a lot of our competitors.

A chatbot is only as good as the data you provide it.

It’s also as much a design problem as a technology problem. Each workflow needs to be thought through carefully to lead to the desired outcome. This is one of the best calls I think I have ever made as the CEO of this company, and we are actually doubling down on our delivery team’s efforts.

chatbot

Q 6. Could you share any analytics on what percentage of requests are being routed through to live chat and how much is being resolved via the chatbot itself?

~90% are done through the bot, 10% go to live chat

However, important thing to note is that amongst the 90%, there may be about 10% or so that are answered incorrect. These are cases where clients take a conscious call that they don’t want to have live agents at all and are okay with even incorrect answers for the long tail of queries.

Q 7. Broadly, where is conversational AI at the moment and where is it heading? What are the areas open to innovation?

Could write an essay on this 🙂

At a high level, this is my favorite way to describe it:

Source: Aakrit Vaish

And at Haptik, we have literally lived this cycle since 2013. The circle above represents 2019 and the next few years are going to be the market adoption phase. We see the power of voice technology coupled with languages (particularly in a market like India) lead the next phase of innovation.

Interview Parts: Part 2 Part 3

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Introducing #AiBoss Series: In-depth Interviews with AI Leaders

AI has become the next ‘I can play guitar’ buzzword.

Every company and every developer that has used even basic pattern matching technique (thank you, PERL) is now claiming to be an AI expert!

We, at NextBigWhat, are attempting to drive forward the conversation around Artificial Intelligence in India beyond headlines that scream for attention but don’t offer much, buzzwords that make your head buzz after a while, and countless utopian tales that vie for your eyes only to leave you with a scratching head and a lingering itch to actually get to the meat of the matter.

AI BOSS SERIES: Interview with AI leaders in India
AI BOSS SERIES: Interview with AI leaders in India

On the one hand there is heady mainstream buzz but nothing in-depth, while on the other, corporates and startups are being feted for incremental AI advancements which pale in comparison to the kind of progress we hear and see from the two giants in this space: the US & China.

What exactly is happening in the AI space in India?

To cut through the PR and the noise, we have decided to conduct in-depth, incisive interviews of top leaders of AI-based companies across sectors in India, from B2B to B2C, and draw out actual insights to help you get a true picture of the artificial intelligence terrain in India.

In this spirit, the #AIBoss series intends to educate, inform and elevate our readers understanding of the subject as well as the space. If you’re part of the leadership team of an AI based product, from enterprise or startup, willing to share your AI learnings – then reach out to us and become part of this initiative (you can apply using this form).

Note: The series starts March 1st week.


We are also seeking partners/series sponsor : If you are a company who is keen on promoting AI and is looking for a great platform to showcase your AI solution, please get in touch.

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