Getting to yes - What investors look for in big data & AI startups
summary
Investors prioritize concrete advantages: a clear day-one ROI that pays back within a year, a founding team mixing deep ML chops and domain expertise, and a defensible proprietary data asset that is frequent, rich and hard to replicate — “better data trumps better algorithms.” Infrastructure bets require a large enabled TAM; applications need pilots and customer case studies and can reach seven-figure ARR. Early human-in-the-loop is fine but firms target >50% gross margin with a path to 70–80% software margins.
AI-written summary · about
chapters (5)
- 0:00Start
- 2:38combine technical excellence with domain expertise
- 5:41evaluate machine learning infrastructure companies differently than vertically focused applications
- 10:04find the exact right domain expertise for your team
- 12:42finding domain expertise
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