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Ag-tech platform Praman goes live to facilitate digital trades of agricultural produce

Ag-tech platform Praman goes live to facilitate digital trades of agricultural produce

The Start-up expects Praman to hit a monthly GTV of $100 million within the next two quarters that would make it the largest agri-trade exchange in India.

Intello Labs founders (Left to Right)- Nishant Mishra, Milan Sharma, and Himani Shah Intello Labs founders (Left to Right)- Nishant Mishra, Milan Sharma, and Himani Shah

Agri-tech venture Intello Labs has announced the launch of 'Praman', which will function as an agriculture produce trade exchange platform with integrated quality assessment. Currently, the platform facilitates spot-trading and e-auctioning of agri-commodities including cardamom, onion, garlic, pomegranate, apple, potato, and tomato.

The product which was functioning in stealth mode over the past few months was formally launched on Thursday, said a release by the agtech venture.

"Within a few months since its launch, Praman has already achieved a monthly Gross Transaction Value (GTV) of $40 million. Praman has successfully re-engineered auctions and trade through AI-based quality assessment, making them data-driven and digital," stated the release.

More importantly, the start-up is expecting Praman to hit a monthly GTV of $100 million within the next two quarters that would make it the largest agri-trade exchange in India.

"We are pleased to give the entire trading process a digital makeover, driving geographic expansion and market outreach," said Milan Sharma, CEO & Co-founder, Intello Labs.

This assumes significance as the subjectivity of manual grading causes drastic fluctuation in pricing decisions during auctions. For instance, the start-up's quality assaying technology brings over 95 per cent accuracy to cardamom quality grading as opposed to about 70 per cent using manual methods.

Apart from its presence in India, the venture also has a presence in the United States, Europe, and Southeast Asia and utilises computer vision, machine learning, and AI to digitise food quality assessment and control.

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