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Is your AI-built app production-ready?

You shipped fast with AI. Before you scale it, raise on it, or hand it to a team, get an independent senior review. It tells you whether the code behind your vibe-coded MVP is production-grade, or a liability.

Corporate buyers know this as code assurance or technical due diligence.

What the audit answers

One question a demo cannot answer: is this codebase real, safe, and maintainable? You get a clear verdict: go, fix-first, or no-go. Plus a prioritized remediation roadmap and a rough cost and time to production-grade.

Who it is for

Founders, pre-raise or pre-scale

You built the MVP with AI. Before you raise or hire engineers, know what is real and what needs rebuilding.

Corporate assurance

Governing shadow AI, or signing off a vendor's delivery? You get an independent acceptance gate with an audit trail.

Investor technical due diligence

About to fund or acquire an AI-built product? We tell you whether the codebase is an asset or a risk, before you sign.

What we examine

Vibe-coded software fails in predictable ways. We check each one.

  • Does it work, or only demo-work? Real edge cases, not the happy path.
  • Security and secrets. Hardcoded keys, missing auth, injection points.
  • Correctness. Code that looks right but computes the wrong result.
  • Tests and CI. The safety net that lets you change code without fear.
  • Hidden tech debt. Duplication, dead code, and invented dependencies.
  • Data and GDPR. Where user data goes, and whether that is lawful.
  • Scale and cost. Behavior at ten times the load, or the cloud bill.
  • Supply chain. Risky or incompatible open-source packages and licenses.
  • Maintainability. Can a human team safely take this over?

Why not just run a scanner?

SonarQube and Snyk are useful. They find known-pattern issues cheaply and run in your pipeline. They cannot judge whether the logic is correct, the architecture will hold, or a team can maintain the result. A vibe-coded app can pass both and still be unfit to ship.

We use those tools as inputs. We sell the judgment they cannot provide.

Background reading: how we practise AI-assisted engineering instead of vibe coding, and where the hidden tech debt in vibe-coded apps collects.

Modernizing a legacy app?

Same discipline, applied to change. Before we touch legacy code, we build a test harness that proves the current behavior. Then we modernize against it. You get a provable safety net, not a big-bang rewrite.

The deliverable

  • A go / fix-first / no-go verdict
  • A prioritized risk report
  • A remediation roadmap
  • A rough cost and time to production-grade

How it runs

  • Fixed scope, fixed price
  • Senior review, about one to two weeks
  • Your code stays with you
  • Clear next steps you can act on

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