Technical Due Diligence: Preparing Your Codebase for Fundraising
What investors' technical due diligence actually looks for — and how to prepare an AI-built codebase for it.
Not every fundraising round includes a deep technical review, but enough do — especially at Series A and beyond, or when a deal involves a technical advisor — that it's worth knowing what they look for. The good news is that most of what's checked overlaps heavily with general production-readiness, so preparing for one prepares you for the other.
This is especially relevant for startups whose early product was built quickly with an AI tool — which is increasingly normal, but worth being upfront about and prepared for.
What Technical Due Diligence Actually Checks
Reviewers typically look at a handful of consistent things: how the codebase is structured and whether it's maintainable, how access control and data security are handled, whether there's any testing or CI, and how dependent the product is on a small number of people (or on tools/services that might be hard to replace).
Common Red Flags in AI-Generated Codebases
These aren't unique to AI-generated code, but they show up disproportionately often in fast-built MVPs.
- Missing or overly permissive database access controls (e.g. Row-Level Security gaps in Supabase)
- API keys or secrets committed to the repository or exposed client-side
- No automated tests, and no CI pipeline
- Hardcoded configuration that differs between 'environments' that don't actually exist separately
Documentation Investors Expect to See
You don't need extensive documentation, but having a short written overview — architecture, key dependencies, how deployment works, and known limitations — saves time and signals that the team understands its own system, which is itself a positive signal.
How Long Does Preparation Take
For a typical AI-built MVP, a focused review-and-fix pass addressing the items above usually takes one to two weeks — similar in scope to our AI App Rescue package, which was designed around exactly this kind of production-readiness gap.
Frequently Asked Questions
Is it bad to tell investors our MVP was built with an AI tool?
Increasingly, no — it's common and often seen as a sign of capital efficiency. What matters more is whether you're aware of the gaps that come with that approach and have a plan (or have already addressed them).
Do we need this even for a small pre-seed round?
Formal technical due diligence is less common at pre-seed, but the underlying issues (security, access control) are worth fixing regardless, since they affect real users too — not just investors.
Can you do this review without taking on the fixes too?
Yes — a review can be scoped on its own, though most teams choose to address the findings as part of the same engagement since the context is fresh.
Related Reading
AI-Generated Code Security Vulnerabilities
Common security gaps this kind of review uncovers.
Learn moreHow Much Does It Cost to Productionize an AI-Built App?
What a readiness pass typically involves and costs.
Learn moreAI App Rescue
Our fixed-price package for production-hardening AI-built apps.
Learn moreAI App Rescue
Take your Lovable, Bolt, or Cursor prototype to production. We fix auth, database architecture, and performance in 2 weeks.
Preparing for a raise?
We can review your codebase against what technical due diligence typically checks, and fix what needs fixing — fixed price, focused scope.
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