Know what to build and what to buy
Deal-sourcing logic and investment thesis models are proprietary to each firm's strategy, so building in-house makes sense. LP obligations, compliance tracking, and entity governance are just as critical, but they demand something different: these workflows cut across legal, compliance, finance, and IR at once, and getting them wrong carries real risk. That's where purpose-built tools win.
Where Purpose-Built Wins
- Precision of Outputs: Get audit-ready outputs with traceable, verifiable sources, not a plausible-but-wrong answer that generic LLMs can't catch.
- No Maintenance Burden: Skip the reprompting and revalidating that comes with every model update. Anthropic and OpenAI alone have shipped multiple major updates since December 2025, and each requires a new round of testing and validation.
- Compliance: Keep pace with shifting requirements like the SEC's 2026 AI exam priorities without pulling engineering off your firm's competitive edge.
GreyLion Capital
"AI is going to affect everything that we do, so our preparation is about being smart – understanding the technologies, how they can help us, and avoiding tools that won't be usable or valuable in the future, while being thoughtful about where we spend our time and money."
Battery Ventures
"Ontra has freed up our investment team to focus on their highest priority work, which is finding good deals for investment. If we can give them each just a few hours a week, that can have a huge effect. And that is invaluable."
Ontra
"[With generic AI] the structural problems are worse than they appear. Context windows are finite. The session isn’t durable. The analyst who uploaded those side letters on Tuesday has a chat thread. The compliance lead preparing for Wednesday’s audit is starting from scratch. There is no audit trail, no version control, no permanence. A prompt is not a repository."
