Five startups have been adjudged the winners of the Startup India - WhatsApp Grand Challenge and will each take home prize money of Rs 35 lakh.
The programme was first announced in October last year and 10 startups were shortlisted from a pool of 1,700 entries, 70% of which were less than three months old.
These startups then made presentations to a jury which included Vani Kola, managing director of Kalaari Capital; Shailesh Lakhani, managing director at Sequoia Capital; Deep Kalra, founder at MakeMyTrip; Harsha Kumar, partner at Lightspeed Ventures; and WhatsApp India head Abhijit Bose.
Below is a snapshot of the winning startups:
MedCords: The startup is based out of Kota and uses technology to provide affordable and quality healthcare to rural and semi-urban populations. It digitises patient records and prescriptions, providing e-consultation and flagging insights based on data science to relevant healthcare authorities. The service can be accessed by feature phone users and is available across 2,000 villages.
Melzo: Headquartered in Surat, the startup provides virtual reality services. The cloud-based platform which works on extended reality caters to over 140 brands and small and medium enterprises. It enables content consumption for low-end devices and has garnered over 3 million views across 200 countries.
Javis: Based in Mumbai, the startup provides an artificial intelligence platform for enterprises. It offers solutions across sales target setting, demand planning and promotion optimisation. The platform also enables a WhatsApp-based conversational AI platform.
Gramophone: The agri-tech company based in Indore provides information and intelligence inputs to farmers ranging from crop protection, crop nutrition, seeds, implements and agri-hardware at their doorstep. Gramophone claims to help farmers reduce cultivation costs by 15-20% and increase production by 30%.
Minion Labs: Based in Bengaluru, the startup helps users track their electricity consumption through its smart meter. The device leverages machine learning to train its algorithm and can predict energy consumption by each device. The plug-and-play solution is deployed with organisations and individual users.