In 2026, technical due diligence for an AI startup at seed goes far past "does the demo work." Investors now open the hood: which models you use and whether they are self-hosted or API, your unit economics and inference cost per user, where your data comes from and whether it is defensible, and — the one that kills deals — whether you actually own your code and IP. Two things that used to appear at Series A are now effectively mandatory at seed: SOC 2 and an AI bias audit. Here is exactly what a technical DD checks, and how to walk in ready to pass.
A modern AI diligence covers five areas. Know what "passes" in each before you take the call.
| Area | What they ask | What passes |
|---|---|---|
| Model & performance | Which models? Self-hosted or API? How do you evaluate quality? | A clear eval methodology with benchmarks, not vibes |
| Unit economics | Inference cost per user? Gross margin at scale? | Known build and run costs, with a path to margin |
| Data | Where is your data from? Is any of it proprietary? | Documented provenance and a real data moat or licensing |
| Architecture & code | Who owns the repo? How much tech debt? | Founder owns 100% of IP and the GitHub repo |
| Compliance | SOC 2? AI bias audit? HIPAA/PCI if relevant? | SOC 2 started, bias audit done, regulated surfaces mapped |
Notice the shift: diligence used to stop at product-market fit and growth. For AI it now weighs model performance, compute efficiency and data quality as first-class questions — because those decide whether the thing scales without the margin collapsing. The run-cost question in particular catches teams off guard; we break it down in the real cost of running an AI product.
Increasingly, yes. SOC 2 — at least Type I or visibly in progress — plus an AI bias audit is now expected at seed, not deferred to Series A. The pressure comes from both sides: investors want to see security maturity, and your first enterprise buyers will ask for the report before they sign. Starting SOC 2 early is cheap; scrambling for it mid-raise or mid-deal is expensive and slow. If you are building toward it, our guide to SOC 2-ready software covers what to bake in from the first commit.
Code and IP ownership. If you outsourced the build and cannot show that you own the repository, the assignment of IP, and the infrastructure, it is a deal-killer — investors assume the worst about what they cannot verify. The other common red flags: a thin wrapper over someone else's model with no data or workflow moat; run costs nobody has measured; and an AI feature with no evaluation harness, which signals you cannot tell when the model breaks. Each one is fixable, but only if you find it before the investor does.
Build investor-ready from day one instead of cleaning up under deadline. The checklist:
We build investor-ready MVPs where you own the code, IP and repository from day one, on a foundation designed to survive exactly this conversation — at a fixed price, senior team, no juniors on your product. Our free Investor Tech Due-Diligence Kit (on the MVP cost page) lays out what investors check and how to be ready. Preparing to raise? Book a 30-minute readiness review and we will flag the landmines a technical DD would find.