Agritech Startup Agrowave Looks To Create Data-Driven Farms In India By Fixing Distribution

For decades, India’s small and marginal farmers have suffered the impact of the inefficiencies in the supply chain and have struggled to get a fair price for their produce, leading to hoarding and food wastage. It is estimated that India loses close to $13.7 Bn a year, approximately 7% of total food production, due to these supply chain hurdles. 

While startups have tried to bridge the gap by trying to reach farmers deep in India’s interiors, the coverage is far from widespread. Gurugram-based Agrowave is looking to maximise this with its mobile pickup stations to reach farmers at the farm gate instead of bringing them to mandis and other markets. 

Agrowave, which today (September 28) raised $500K in Pre-Series A funding from US-based angel investor Sekhar Puli, is looking to create an integrated supply network through these mobile pickup stations (MPS) to back its predictive farm analytics play as a way to solve both production and the distribution for farmers. 

Puli, who is cofounder of Rean Cloud, a US-based cloud systems integrator (acquired by Japan’s Hitachi Vantara in 2018), is the second investor in the company, which had previously raised $700K in a seed round from mobile app and cloud solutions company Daffodil Software. 

Agrowave’s Distribution-Focussed Data Play

Competing with the likes of Ninjacart, WayCool Foods, Crofarm among a slew of other agri-focussed supply chain startups, Agrowave was founded by IIT Delhi alumnus Anu Meena in 2017. 

The funds would be used for enhancing the company’s technology capabilities for the prediction models which are linked to the MPS network. The models help farmers price their products optimally and streamlines supply chain across various commodities. Besides these, Agrowave will use the funds for route mapping of the pickup mobiles, its various collection centres, which act as distribution hubs, and warehouses. 

Hemendra Mathur, a venture partner at Bharat Innovation Fund and a mentor for Agrowave believes the company’s farmer-to-mandi (F2M) and mandi-to-consumer (M2C) model is unique in many ways. “There is end-to-end traceability of the product with quality control and little loss in storage and transportation,” he said, adding that Agrowave is simplifying the agri supply chain at the grassroot level with its full-stack farm-to-fork model. 

Agrowave was started with the aim of providing better returns to small and marginal farmers. The company buys fresh produce directly from farmers through its network of mobile pickup stations at farm gates in villages. Farmers can connect to the pickup stations with the AgroWave mobile app and the startup then sells the produce to businesses, restaurants and at markets. In the last year, the company claims to have earned 60%-70% of its business through its farm-to-mandi chain and 30-40% through the demand-side chain. 

In addition to this, Agrowave said that it is working on a price prediction model for farmers to minimise on-ground revenue leakage and plans to scale this model across villages in the country. 

The primary objective of the MPS model is to simplify data collection and help farmers earn more income. “At present, we are able to give farmers a 15%-20% rise in their income,” claimed Meena, comparing its model to the traditional supply chain. 

The company says it is working with close to 3.5K farmers, 250 traders and 300-400 plus businesses in Delhi NCR, Haryana, Punjab and other states in north India. The pickup vehicles are leased depending on the demand in each region and each mobile station is linked to a collection centre, which then supplies to the nearest mandis and businesses. 

How Agrowave’s Predictive Models Work

In terms of the predictive model, Meena said that Agrowave is currently building three prediction models based on smart route mapping, price prediction engine and data intelligence-driven supply-demand. For instance, in smart route mapping, the company looks to map its MPS, collection centres (CCs), mandis and warehouses based on multiple variables such as distance travelled, volume, origin, connectivity and demand. 

In the case of the price prediction engine, the model is customised for every MPS. The supply-demand mapping system would be able to track the farmers, origin of produce, the commodity, volume of supply and demand to boost income and productivity. The company also partners with seed suppliers, agri-financial companies and fertilizer makers to ease farm input procurement. 

“Since we are operating across multiple villages, we are getting the data of farmers in terms of how much they are selling, what they are selling and when they are selling depending on the seasons. However, this is a long-term game. At the moment, our primary focus is to build a sustainable supply of fruits and vegetables by procuring directly from the farmers and selling it to the end consumers, mandis and businesses.” 

Currently, Agrowave is a 20-employee company and in FY20 it has reported $3.7 Mn in revenue, which is over 50% higher than the $2.1 Mn in FY19. 

 

In the coming months, Agrowave is looking to extend its MPS to different villages to build a strong network of farmers and further expand its presence to Rajasthan, Madhya Pradesh, Uttar Pradesh, Haryana, Maharashtra and Bihar. “We are looking to raise $10 Mn in funding by 2021 to further scale-up,” revealed Meena.