FasalForward founder Ansh Jalan with farmers in Jalgaon, Maharashtra.
When a 17-year old Ansh Jalan travelled from Mumbai to Jalgaon, a district known for Banana farming in Maharashtra, to test his thinking around crop price prediction, he expected the conversation with farmers to be about tomorrow's prices.
Instead, the farmers pointed him towards a more immediate problem.
They did not just need to know where prices might go tomorrow. They needed a simple way to know what their crop was worth today, and how that price compared with what they could get in other mandis.
That insight would shape the direction of FasalForward, an agricultural information app that Jalan had begun developing on May 29, 2026.
After gaining basic insights during his internship at KisanKonnect, a farm - to - home farmers' digital market for fresh vegetables and fruits, Jalan had started working on FasalForward with the idea that better access to agricultural price information and predictive tools could help farmers make more informed decisions. But his visit to Jalgaon brought him face-to-face with the realities behind the data.
Over five days, conversations with farmers and people involved in banana procurement at Jain Irrigation Systems highlighted the complexity of agricultural pricing. Weather, arrivals, demand and crop quality can all influence the price of a crop, making reliable prediction from historical data alone difficult.
But the conversations also revealed a more basic information gap.
Farmers told Jalan that they did not always have an easy way to find out what their crops were fetching in other mandis. Without that information, even a farmer who wanted to make a simple decision about whether to sell today or wait could be operating with limited visibility.
"I thought farmers had access to everything, and that the one unique thing I could offer was price prediction," Jalan said. "A lot of them told me that they did not have access to a lot of this mandi information at all."
For Jalan, that became a critical insight.
The question was no longer simply, "Can we predict tomorrow's price?" It was also, "Can we give a farmer reliable information about today's price, in a form that is simple and accessible?"
That insight further influenced how Jalan has developed FasalForward.
FasalForward founder Ansh Jalan with farmers in Jalgaon, Maharashtra
A Class - 12 student at the Cathedral and John Connon School in South Mumbai, Jalan is the app's sole developer. FasalForward brings together daily mandi prices from Agmarknet, the agriculture ministry's agricultural market reporting network, along with weather information, sowing window guidance and crop recommendations.
The app currently covers 18 crops across Maharashtra, Karnataka, Punjab, Haryana and Uttar Pradesh, with information available in Marathi, Hindi and English.
Its predictive model remains an important part of the platform. But the Jalgaon experience helped Jalan understand that prediction needs to sit alongside something more fundamental: access to current market information.
The feature that generated the strongest response from farmers in Jalgaon was therefore considerably simpler. A screen showing what a particular crop was selling for that day across different markets, in the farmer's own language.
For farmers, that information can have a direct financial consequence.
One grower Jalan met described selling about 50 tonnes of Chana before watching the market rate rise by roughly Rs 100 a quintal within a fortnight. Across 500 quintals, the difference amounted to about Rs 50,000.
The farmer had no straightforward way to compare the price available to him with rates in other markets. That left him with little information on which to base the decision of whether to sell or wait.
Jalan added Chana to FasalForward after the visit. But the episode also revealed a challenge that the app itself still has to solve. For Jalan, that gap is an evidence of the larger information problem he is trying to solve. FasalForward currently has a complete price history for Chana only in Haryana and Punjab. Maharashtra, where the farmer sold his crop, has just one recorded price.
The Jalgaon visit was arranged by Ambika Jain of Jain Irrigation Systems, whose family knows Jalan's. The farmers he met grow bananas for the company. Conversations with growers and procurement staff also pointed to a broader opportunity: a service that could bring together reliable market information from mandis across India could have significant practical and commercial value. It becomes all the more relevant in the present drought - like condition that is looming over Maharashtra and where the farmers are already stressed. In such situations, they need precise farming directions for pre - empting their risks and losses.
"That showed me how gate-kept information is in agriculture," Jalan said.
The experience also made Jalan more cautious about the role of prediction itself.
Mandi arrivals can be irregular, reporting can be patchy and a day's quoted price can vary with the quality of the lots being traded. A prediction can therefore be useful only if its performance is measured against what actually happens in the market.
Jalan has built systems into FasalForward to do exactly that.
The app compares predictions with actual prices and records errors at one, seven, 14 and 30 day intervals. Jalan has also written a separate script to test whether the system's own reporting could make the forecasts appear more accurate than they are.
"I went in thinking prediction was the valuable part," he said. "The valuable part turned out to be showing someone today's rate in his own language. Prediction is the thing I have to keep proving."
FasalForward is still an early stage project. It is free, carries no advertising and has no subscription or revenue model. Its coverage remains incomplete, and Jalan makes no claim that it can solve India's fragmented agricultural information system.
For now, he is expanding the app's coverage while testing whether its predictions hold up against what actually happens in the market.
What began as an attempt to use technology to anticipate agricultural prices is evolving into something broader: a platform designed to give farmers a clearer view of both where the market stands today and where it may be heading tomorrow.
Jalan travelled to Jalgaon looking to test whether technology could help predict tomorrow's prices.
The farmers he met helped him understand that before tomorrow can be predicted, today's price needs to be visible.
