Data Sutram, a Kolkata based tech start-up in its early stage, raised Rs 2 crore from Indian Angel Network, the funding round was led by Indian Angel Network (IAN) angels – Uday Sodhi, Mitesh Shah and Nitin Jain.
Founded in 2018 by three Jadavpur University engineering graduates Rajit Bhattacharya, Aisik Paul, and Ankit Das, Data Sutram is an AI-backed platform that gathers intel from external data to provide location-based data intelligence.
Rajit Bhattacharya, Co-founder, Data Sutram, said, “We are delighted to get IAN on board as an investor, and will leverage the capital infusion to strengthen our platform in providing enhanced services to our consumers.”
Uday Sodhi, Lead Investor at IAN, said, “It is heartening to see startups such as Data Sutram using cutting-edge technology, tapping unstructured data and insight to create innovative solutions for the B2B market. Its unique, tech-led approach is solving some of the most pressing problems for a large consumer base by developing a predictive analytics solution to help bridge the demand-supply gap.”
The B2B-focussed start-up claims that it helps a business by pinpointing new locations to expand, improving the performance of existing assets (both physical and digital), and micro-targeting the right audience for the product. Starting at 12 data sources, the engine currently taps into over 200+ data sources in a span of six months to garner intelligence.
In 2020 previously, Data Sutram was a part of 100X VC’s first class of 20 companies and raised Rs 25 lakh from 100X.VC.
At present, the start-up is focussed on retail-specific sectors such as pharmacy, FMCG, and grocery, with plans of expansion into the BFSI, agritech, and media and entertainment in the future.
As per the start-up there is a massive availability of valuable insights that lie in the form of unstructured data from multiple resources. These data need to be processed, cleaned, geotagged, and converted into usable data, that can be readily utilised by a business. And, Data Sutram aims to resolve this problem as it uncovers raw data sources and calculates socio-economic parameters like demography, ethnicity, affluence, spending capacity, and a host of other parameters to understand a location.