AgTech Startups

Agritech start-ups, from Accel-backed Agrostar to IvyCap-funded RML AgTech, among others, are investing approximately Rs 5 crore each in building ground breaking image recognition technology that enables farmers to receive real-time data on the pest or disease that has affected a crop, offering solution in a minute, by just using a picture clicked with a smartphone.

While RML AgTech have up to 8,000 farmers across Maharashtra and other states already using the technology feature to find problems with tomatoes and other crops. Players like Agrostar are investing in creating the technology and carrying out pilot programmes in Gujarat.

RML AgTech offers a basic version of the app free, but charges anywhere between Rs 1,000 and Rs 3,000 annually for the app with the image-recognition feature. Agrostar plans to provide the image recognition feature free to farmers.

Agrostar plans to scale up and develop the image recognition technology over the course of this year. They also recently raised $10 million in a funding round led by Accel Partners.

To help farmers on pests, crop diseases, start-ups like Agrostar, RML AgTech use imaging tech. Cofounder of Agrostar, Shardul Sheth said, “We are targeting crops like cotton and groundnut, we are getting data in terms of images from the farmers themselves. More than technology, the biggest challenge currently is having a repository of images that can be mapped to the image that a farmer has taken on his phone and determining the problem and solution in real time, without any manual intervention.“

Over 10 lakh farmers used the services offered by the platform; over 1 lakh farmers have downloaded the app. For its pilot programme, the start-up is targeting less than 1,000 farmers in Gujarat.

The company, which raised $4 million in a funding round led by IvyCap Ventures in January, focuses on identifying pests and solutions related to tomato crops with this feature. The image recognition feature on RML AgTech's paid app, called crop doc, is available in varied regional languages.

The company says it has over 12 lakh farmers using the app. CEO, RML AgTech, Rajiv Tetviya said, “In addition to technology, one needs to have insights. Tomato has close to 48 issues. If one wants to deploy image recognition tech for each problem, you have to have a minimum of 200 different images in the database to reach a 90% accuracy level, but to reach 99% accuracy level, we should have at least 6-700 images per problem. We want to cover all Indian crops by the first quarter of 2018.“