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Sector thesis

AI / ML

Investors backing applied AI, enterprise AI, and ML-native products — not AI as a buzzword.

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What this thesis means

AI and ML investors want companies where machine intelligence is core to the product value, not a slide decoration. That includes enterprise AI copilots, vertical AI workflows, infrastructure and tooling, and consumer products with meaningful model-driven experiences.

In India, many strong opportunities are applied: AI for sales, support, healthcare ops, finance workflows, and developer productivity — often sold as software with clear ROI. Diligence asks what is proprietary (data, workflow, evaluation, distribution), what is rented from foundation models, and how margins hold as model costs change.

Do not pitch “we use GPT.” Pitch the workflow you own, the evaluation bar you beat, and why customers will keep paying when every competitor ships a chatbot.

Who it fits

  • Enterprise AI, vertical AI, and ML-platform founders
  • Teams with domain data or workflow depth
  • Products where AI improves measurable business outcomes

What to prepare

  • A demo of the workflow, not only model claims
  • Data advantage and evaluation approach
  • Gross margin and inference cost story

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