The Indian EV transition is the largest mobility shift in the country's history. The batteries powering it are the least understood component in the chain. Every stakeholder — OEM, lender, operator — makes consequential decisions with broken information. We built enerlytik to end that.
The data exists in Indian field conditions. The understanding did not — because the tools had never been built for India.
Models trained on corrupt signals are worse than no model. We apply electrochemical physics to every signal before any ML model sees it.
Indian operating conditions are not an approximation of lab conditions. Every specification derived from lab cycles is wrong for this market by a measurable margin.
Data that does not produce a specific decision for a specific stakeholder is not intelligence. It is overhead.
We say what we know. We say what we do not know. We say when that changes.
IIT Kharagpur · Strategy, product, and technology at Vecmocon and Wiom. Enterprise leadership at Microsoft, IBM, and Tata.
IIT Bombay · VP Strategic Business, Vecmocon Technologies · Housing.com · Wiom. OEM and NBFC partnerships.
IIT Bombay · Quant derivatives trader ₹50L+ before architecting our ML pipeline · Published in Nature.
The methodology begins where the intelligence gap is deepest — the Indian EV battery. It extends to every asset in the energy transition.