Benjamin Raja is the Founder and CEO of Farmagain Agro Pvt. Ltd., an AgriTech company transforming agriculture through AI, IoT, and precision farming technologies. With over 20 years of global engineering and technology leadership, he founded Farmagain to help farmers produce more with fewer resources through scientific, sustainable, and intelligent farming solutions.

What was the core belief that drove you to start FarmAgain, and how did it shape your initial days?

FarmAgain, the core belief was that the productivity gap between Europe and India for each crop can be reduced, and Indian farms can be made to produce as much as European farms and with that we can play a significant role in the lives of Indian farmers.

In the early days it was difficult to make farmers understand that their realized productivity is far below the capability of the plants they were growing, and hence we faced quite a bit of resistance, but overtime, they now understand the real gap in productivity partially through the outburst of information available through Internet

What is one ground reality about Indian agriculture that completely changed your perspective after entering the field?

The perspective in everyone’s mind that agriculture is a loss making venture. But when we entered agriculture, we realized this is one of the very few ventures that gives the greatest return on investment. Added bonus was the taxfree income generated by all farms

Can you share a turning point conversation with a farmer or mentor that significantly changed FarmAgain’s direction?

A farmer tells his son: “My son, pls study well and get a good job. I don’t want to see you go through the same sufferings I am going through. I really want you to have a decent life, drive a car like these uncles. Study is the only thing that can help you get out of farming”

What was the single biggest frustration in traditional farming that pushed you to build a tech solution?

Lack of awareness of precision farming principles and benefits, and consequently, farmers using traditional methods on high yielding crops that are actually meant to produce more but also feed more. But when the farmers fail to feed these plants to their actual needs they produce 10-20% of what they were actually capable of

Farming is not a failure, it's the farming methodologies that make a farm and a farmer fail.

Why did you choose to build in-house solar hardware and private LoRaWAN networks instead of relying on third-party tech?

Third-party tech was too expensive, typically charged on a per message basis. But a farm would exchange hundreds of messages a day making it unviable. Secondly, public LoRaWAN infrastructures are still not available in remote villages.

Similarly the thought behind going solar was to make sure the tech doesn’t fully depend on the grid availability

How does GroTron use soil and weather data to scientifically enhance plant photosynthesis rather than just saving water?

GroTron is one of the very early users of AI, receiving an award for using AI in agriculture in 2018.

GroTron’s AI engine predicts when soil moisture will lose its balance between air and water, and will automatically schedule irrigation in such a way that the balance is always maintained. Photosynthesis can be effective only when the rootzone air-water balance is maintained.

How does GroTron’s automatic EC and pH correction mechanism function autonomously inside the fields?

EC and pH are two key parameters that either keep the rootzone in comfort so that they can uptake all available minerals, or when they are out of range, the roots don’t uptake anything at all.

GroTron has the capability of ingesting the right quantity of different fertilizers and keeping the EC and pH constant in the irrigation water line ensuring the plants are truly able to uptake minerals which ensures plants ability to grow as per their genetic ability

How does the Google Gemini-powered chatbot in GroTronX process crop photos to provide real-time remedies to farmers?

It’s a tool built using the combination of Gemeni and Claude, which will analyze the photos and identify all pests, diseases and nutrient deficiencies and identify remedies by taking into account the hyperlocal weather aspects. This tool can also provide a reasonable pest prediction. Users can also chat to optimize the remedies further.

How did your team break the psychological barrier and win the trust of traditional farmers for autonomous farming?

We earned farmers’ trust by demonstrating measurable results in the field. Higher crop yields, healthier plants, and significantly lower water consumption helped farmers experience the benefits of autonomous farming firsthand. These visible outcomes gradually built confidence and encouraged wider adoption of our technology.

What unexpected technical lessons did you learn while deploying your IoT devices across diverse agro-climatic zones?

One of our biggest learnings was that agriculture cannot rely on a one-size-fits-all approach. Every region has unique climatic conditions, soil characteristics, and crop requirements. This reinforced the importance of building hyperlocal, data-driven solutions that can adapt to the specific needs of each farm and deliver more accurate, reliable outcomes.

What has this intense agritech journey taught you personally about leadership, resilience, and building a startup from scratch?

Agriculture is an area where resilience is the key as the weather is one of the major influencers of the outcome. Hence to prove a method may take months to years. So building a team which has patience and perseverance is the deciding factor for success.