NuSynth Technologies raises Rs 36.5 crore to use AI to redesign chemical making

NuSynth Technologies, a Karnataka-based start-up that uses artificial intelligence to redesign how speciality chemicals are made, has raised Rs 36.5 crore, or about $4 million, in a seed round co-led by Avaana Capital and Shastra VC. The round was reported on Tuesday, October 13, 2026. The company is led by chief executive Poorvank Purohit, a former managing director and CEO of Solara Active Pharma Sciences, and says it will spend the money on research and technology, building its first set of proprietary chemical processes, scale-up capability and a larger team.

Most of the AI start-ups that raise money in India build software for other software companies: chat assistants, sales tools, coding aids. NuSynth sits in a less crowded corner, applying AI to the physical work of making molecules. In chemical manufacturing, the route a company takes from raw material to finished product decides its cost, its waste and how safely it can scale up. Finding a better route traditionally takes many rounds of laboratory trial and error. NuSynth's pitch is that models trained on experimental data can narrow down the options faster, so chemists run fewer, better-targeted experiments.

The choice of pharmaceutical and electronics chemicals is deliberate. Both are high-value markets where a cheaper or cleaner process can make a large difference to margins, and both are areas where Indian manufacturers want to compete more strongly with established global suppliers. A start-up that owns its own processes, rather than only selling a service, can license them or manufacture with partners, which is why NuSynth says it plans to build a portfolio of proprietary processes.

The investors also say something about where Indian venture money is moving. The round is a bet on a deep-technology company that works on manufacturing rather than on consumer apps. For a seed round, Rs 36.5 crore is a sizeable cheque, reflecting the cost of laboratories and scale-up equipment that a pure software firm does not need.

The test ahead is the step every chemistry start-up must take: showing that a process that works in a lab flask also works at industrial scale, reliably and at a lower cost than existing methods.

Short-term: NuSynth will expand its research team and lab capacity and start building its first proprietary chemical processes in its two chosen sectors.

Long-term: If its AI-guided approach cuts the time and cost of developing new manufacturing routes, it could help Indian makers of drug ingredients and electronic chemicals compete on price and sustainability, and it could draw more investment into AI applied to physical industries.

Who is affected: Chemists and engineers looking for work in deep-tech start-ups, pharmaceutical and electronics manufacturers that may license or co-develop processes, and investors watching AI move beyond software.

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