Exclusive Interview with Gaurav Asthana, CTO of Gramophone

Over the past five years, more than 3,000 agritech startups have entered the scene. However, their combined revenue was less than $100 million. This shows there's room for more players in the sector as no company can have a monopoly and effectively address all the challenges. Gramophone is a full-stack Agritech platform for solving the end-to-end needs of farmers. Analytics Insight has engaged in an exclusive interview with Gaurav Asthana, CTO of Gramophone.

1. Brief us about the CTO of Gramophone and his contributions to the company and the industry.

I have close to two decades of extensive experience in web application development, E-commerce websites, Fintech systems, Agritech, Job sites, and more, with technology companies. I have deep expertise in working on high-traffic applications and improving performance and scalability with innovation and new technologies.

Gramophone is a full-stack Agritech platform for solving the end-to-end needs of farmers. We have built tools to help farmers with Agri intelligence, advisory on best farming practices, procuring Agri inputs, arranging farm equipment, selling crops, etc. We have also built android apps for people in the overall ecosystem -farmers, retailers, and rural entrepreneurs – to help them engage better with farmers.

I started my career with Naukri.com (Info Edge) and had a long stint of more than 10 years there. Then I moved to 1mg, and later fintech platform Zip loan. Currently, I am leading the technology as Chief Technology Officer of Gramophone (an Agritech Platform). I am an engineering graduate and have done MS in software systems from BITS Pilani.

2. With what mission and objectives was Gramophone set up? In short, tell us about the journey since the inception of the company?

Traditionally, farming practices in India have been based on heuristics with retailers and OEMs playing an outsized role in influencing the sale of farm inputs. There is a clear conflict of interest here- where the sellers would be incentivized to push products that may not necessarily be in the farmers' best interests.

Secondly, no single player has a holistic crop lifecycle management approach. Each player addresses his product or offering (e.g. seed or fertilizer); bringing it all together is a white space opportunity. Thus, customized and scientific (data-driven) support, along with genuine agri-inputs can help farmers from sowing to harvest. This has the potential to increase the income by at least 50% for the farmer.

This was the genesis of the Gramophone. We launched the first version of our farmer lifecycle management tool in the first 12 months of our operations, followed by the launch of our internal ERP for order management, as well as our field app tool for managing the last mile logistics in 2018-19. This was followed by the launch of our Gram Salah tool for real-time agronomy advice in 2020-21. 2021 was also the year when we launched our output business marketplace (Gram Vyapar) – allowing farmers to connect with buyers and sell the products across geographies. This is followed by a community of farmers on the application, making Gramophone a single platform for farm management + Agri input commerce and Agri output market linkages.

3. Tell us how Gramophone is contributing to the IoT/AI/Big Data Analytics/ industry of the nation and how the Gramophone is benefiting the farmers.

Today, a farmer in the Gramophone network can take advice on which crop to grow, how to maximize yield from his farm, how to minimize the usage and costs of input materials, and so on. Gramophone also empowers him with predictive analytics on what is his expected income at the end of harvest.

Traditionally, all this was driven by human experience and filled with biases and subjectivities. Thanks to all the data we have collected (around weather, cropping patterns, the farmer land details, market supply/demand/price dynamics, etc.) and analyzed, now all the farming decisions are data-driven.

This reduces the uncertainty for the farmer and helps him easily get a 30-40% higher income.

4. How is IoT/Big Data/AI evolving today in the industry as a whole? What are the most important trends that you see emerging across the globe from an emerging technology standpoint in the Agri space?

In the Agri industry as well, there are several IoT/Big Data applications. One simple use case is that farmers capture images of crops affected by pest/disease and share them on the Gramophone platform; we can analyze the issues and guide them on corrective steps. Some farmers have also been able to remotely manage irrigation systems (through their mobile phones and on-field sensors), saving time and money.

We have IoT sensors for soil assessment; drones collect land data; satellites provide weather and canopy imagery data; several digital platforms are providing real-time data on market supply and price trends; combining all these data sources, one can arrive at smart insights to guide farming practices and decisions. There is a huge opportunity to bring all these aspects together and build an Intelligent Farming Ecosystem, enabling farmers to run agriculture as a business!

5. AI is projected to be the next market. How is AI contributing to the making of your products and services for your end-user?

At Gramophone, we collect the data of the farm, including but not limited to area, size, location, soil, cropping patterns, soil quality, and harvesting quantity & quality.

With the increasing use of a smartphone, it is becoming easier to capture farmer data (his exact land coordinates, weather patterns specific to his plot, historical market dynamics, etc.). We also have public data available on types of crops, best practices, pest/disease management, market prices, and so on.

We are leveraging data science to bring all this together, and generate simple-to-follow action points for the farmer. The farmer would traditionally be dependent on a few specific individuals to advise him and hence their availability would be a challenge. These pieces of advice were also not particularly reliable. Now, with system-driven analysis, we can look at millions of permutations and combinations, and give a solution at the click of a button.

Apart from core farming issues, we have also looked at areas such as logistics. With our direct-to-farmer approach, last-mile delivery could be prohibitively expensive if not dealt with, carefully. However, thanks to our algorithms, we have been able to optimize the distribution of goods extremely well. Farmers get door-step-service and we can keep our costs low.

Also, since we have a lot of data on production trends and quality of production in different areas (apart from the market data on supply/price/etc.) we can predict well, in terms of where the supply would come next. This is extremely helpful to our customers who are looking for a reliable supply chain. This also helps the farmers get a better sense of what their expected income would be.

6. Could you highlight Gramophone's recent innovations in the AI/ML/Analytics space?

We are working on predictive analytics around farming best practices – taking into account the millions of permutations and combinations of crop/weather/pest/disease / etc… and giving specific recommendations to farmers – sow this, use this amount of water, apply this much of pesticide, and so on.

We are optimizing supply chain/logistics figuring out the optimal route and the right types of interim points, that balance high levels of service satisfaction with low cost.

We are predicting supply and demand for the Agri produce.

7. How have you seen the evolution of the agri-tech industry from a tech adoption standpoint? As you said that you have been with Gramophone from the beginning, how has the growth been?

Internet access is clocking a 13% growth and smartphone usage has risen to 67.6 % in rural markets, with farmers embracing social technology with surprising speed.

In the cardamom belt, farmers are watching YouTube live streams to decide if they want to put up their spice for auction.

Moving onto agronomy advice, there was a time when farmers would solely talk to company officials or local experts. Now, they are actively calling helplines or opening up apps to get advice on how to build healthier soil and increase crop yield.

A medium-holding farmer doubled his farm yield through soil testing and padded the bottom line enough to buy more land in under two years.

The next layer of agritech, e-commerce, where the actual transactions of farm input materials and output occur is picking up fast. This is at around 15%-20% of the farming base, ready to go completely online for doing transactions.

There has been a distinct rise in farmers placing orders online, particularly to procure input materials, because of doorstep deliveries. And a majority of these farmers are making repeat purchases.

Tech usage to sell products online is following a similar path. Farmers are listing their crops on portals and marketplaces because it removes intermediaries who eat into margins. Besides better price discovery, COVID-19 acted as jet fuel, accelerating e-commerce adoption, with more farmers coming online and inviting bids for their crops.

This is expected to grow faster as the layers of payment guarantee and quality inspection modules (which will be a mix of physical + digital) are integrated into the existing market linkages platforms.

8. Can you comment on the Future of IoT/ Artificial Intelligence/ML/Cloud Computing in India in the agri-tech sector?

Some of the large input companies are sponsoring trial usage of drones. This could drive some level of IoT adoption. Some of the IoT soil sensor companies are also exploring usage-based fees (instead of selling the equipment). Such steps could increase adoption by farmers – especially if a partner comes in to help with implementation.

The use of data science is bound to increase a lot more; satellite data is assisting in creating credit risk profiles of farmers. As the digital transactions by farmers increase, these data points will help create a much richer profile of each farmer, and help companies customize their offerings better to their needs. Algo-driven trading on Agri commodities may not be too far either.