AI Services · Measure
Your AI wrote the code. Who checked the tests?
An independent AI code audit that measures whether your tests actually catch bugs, before a launch, a fundraise, due diligence or an acquisition.
Green checkmarks aren't proof
AI coding tools write code fast, and tests that pass. Too often those tests check nothing: placeholders, skipped cases and assertions that can’t fail. AI-generated code passes security checks only 56% of the time (Veracode, 2026). At teams with high AI adoption, bugs per developer rose 54% and pull requests merged without any review rose 31% (Faros, vendor study, 2026).
Coverage reports won’t show any of this. Coverage tells you a line ran, not that a test would notice if it broke.
What you get
AI Code Assurance audit
1–2 weeks per system · fixed fee
- A test-theater scan: tests that pass without checking anything, such as placeholders, skipped cases and assertions that can’t fail
- A mutation snapshot of your critical modules: we plant deliberate bugs to prove whether the tests catch them
- Secret, static-analysis and supply-chain scans
- A review of how your AI coding agents are set up and what they’re allowed to change
- A severity-ranked findings register, every finding challenged by an adversarial second pass and reviewed by a named senior engineer before it reaches you
Hardening sprint
2–4 weeks · fixed fee
- We fix the critical findings, delivered as pull requests reviewed by a Techtura engineer
- We add a minimum set of automatic checks to your build pipeline so they stay fixed. These include secret scanning, a block on placeholder tests and required checks
- Book audit and sprint together: 3–6 weeks end to end, scheduled so the fixes can land before your diligence date. The sprint’s scope is confirmed from the audit’s findings
- It ends with a re-test of the fixed findings and an updated findings register you can share with investors
Proof, not coverage
We plant bugs to test your tests
We measure whether your tests catch bugs. A suite can show high coverage and still miss the bugs we plant.
Every finding challenged before you see it
Every finding survives a second pass that tries to prove it wrong. You get a short list of real problems, not a scanner dump.
Plain-English reporting
We walk your leadership, investors or acquirer through the results in business terms. You hear what the risk is, what it would cost to fix, and what the hardening sprint would fix first.
We ran these checks on our own AI-built code first
10 days
from a 187-agent review of our AI-built code to every confirmed issue fixed, critical and high-severity included
4 of 4
red-team attempts to cheat our test gates, caught and blocked before merge
12
real gaps our planted-bug testing found in tests that had already passed review
~2,000
tests rebuilt to check real behavior instead of fake stand-ins (mocks), with a required check blocking new ones
What our second pass catches
First-pass scanners mark a lot of code clean that isn’t. Our adversarial second pass has caught problems that standard tools missed, including a live credential committed to a repository. That’s the difference between a scan and an audit.
Questions founders and investors ask
Do you need access to our repository?
For the free scan, only if you want us to run it: run the scanner in your own environment and share the results, or give our scan account read-only access to that one repository and we run it for you. For the paid audit, yes: our engineers review your code under access terms you approve up front. Your code is not used to train AI models.
Which languages and CI systems do you support?
Python, TypeScript and GitHub Actions out of the box. Other languages and CI systems are added as part of the engagement.
Can we share the report with investors?
Yes. The report states exactly what was tested, how and what was found, so a technical diligence team can verify it. It’s an engineering assessment, not a legal opinion or a security certification.
Does this replace investor due diligence?
No. It covers what generic diligence rarely tests: whether your AI-written tests actually catch bugs, and whether the code is safe to build on. It sits beside architecture, penetration and licensing reviews, and makes them faster.
What happens after the audit?
The usual next step is the hardening sprint, which fixes the critical findings and locks in the checks. If you’re building something new, the next step is Verified AI Delivery.
A free way to start
The free Code Assurance Scan covers one repository: a scan for tests that check nothing, a secret scan and a planted-bug test of one module. You get a one-page report within 48 hours, and we walk you through it in business terms.
Know what your code is worth before someone else checks.
Ask for the free Code Assurance Scan, or share your launch, raise or diligence date and we’ll plan the audit around it.