You built it fast with AI. That is the point, and it is cheaper than hiring a dev team to build it in the first place. But AI is not there yet: it ships logic flaws, security holes, and overlooked edge cases with total confidence. Before you put it in front of customers or investors, have someone who breaks software for a living make sure it is actually good.
Get your vibe-coded app reviewedMost people who call us about this are at the same moment: the thing is built, the demo goes well, and they are about to put real customer data into it. Then the question lands. Do we actually know this is okay?
This is not an argument against building with AI. Build with AI. The tools are genuinely good at producing working software quickly, and that is why this service exists at the price it does. But they are not there yet on the things that only show up under pressure, and they never tell you when they are unsure. The output looks identical whether it is right or wrong. That is the actual risk.
We QA, security-review, fuzz, and penetration test your vibe-coded product, then hand you a clear list of what is broken, what is exploitable, and how to fix it. Testing is delivered with our offensive-security partner and led by a published security researcher with 6 CVEs, so the findings reflect real attacker behavior rather than a checklist.
Think about what you skipped. Hiring engineers, months of build time, the salary or the agency invoice. AI did that part for a fraction of the cost, and it did it in a fraction of the time. That saving is real and you should keep it.
A review is a defined, one-time cost on top of a build that already came in far below what it would have cost conventionally. Add the two together and you are still well under the old number, and now you know what you are shipping. You are paying for the one thing AI cannot do yet: know what it got wrong.
The alternative is finding out later. A leaked customer record, an auth bug in front of your first enterprise buyer, or a rewrite six months in because the foundation was never checked. Those are not fixed-cost problems. Send us the app and we will scope the review before you commit to it.
Written to be acted on. You can hand most of it straight back to your AI tool and have the fixes made the same way you built it.
The QA findings: broken flows, wrong logic, edge cases that fail. Reproduction steps for each one, so nothing is a guessing game.
The security findings, ranked by what an attacker could actually do with them, not by CVSS score alone. Proof, not theory.
Specific remediation for each finding, in priority order. Clear enough to paste into your AI tool or hand to a developer without a translation layer.
The pen test portion can be scoped and reported as evidence for SOC 2, ISO 27001, or a buyer's security questionnaire, so the same work answers the next customer who asks.
Tell us what you built, what it holds, and who is about to use it. We will scope the review and tell you honestly how worried to be.
Get your vibe-coded app reviewedIt is a QA, security review, fuzzing, and penetration test of software you built with AI coding tools. AI is fast but still ships logic flaws, security gaps, and overlooked edge cases. We review the AI-generated code, fuzz it, and pen test it so you can ship with confidence, still for far less than hiring a full development team to build it from scratch. It is aimed at startups and anyone shipping vibe-coded products.
The pattern we see is confident code with gaps underneath. Missing authorization checks, so an endpoint authenticates the user but never verifies they are allowed to touch that record. Logic flaws, where the happy path works and the edge cases quietly do the wrong thing. Silent omissions, where the model simply did not write the check you assumed was there. Unsafe defaults carried over from training data, and the auth gaps, injection, and secret leaks AI routinely introduces. None of it looks wrong on the screen, which is the problem.
That is the whole point. Building it with AI already cost you a fraction of what an engineering team would have. A review adds a defined, one-time cost on top of that and still lands well under what building it conventionally would have run. You are paying for the part AI cannot do yet, which is knowing what it got wrong.
No. We work from the running application and the code, whatever produced them. The failure patterns are broadly similar across AI coding tools, and we test the software in front of us rather than assuming anything about how it was written.
The default deliverable is a clear, prioritized list of what is broken, what is exploitable, and how to fix it, written so you can hand it straight back to your AI tool or a developer. If you would rather we make the fixes ourselves, our custom development team can, as a separate scope.
Yes. The penetration testing portion can be scoped and reported to serve as evidence for SOC 2, ISO 27001, and buyer security questionnaires. If a customer is asking for the whole framework rather than just a test report, our compliance team handles readiness and audit prep end to end.