Case Studies
Real audits. Clear outcomes.
These are working sessions on real products: what we looked at, what surfaced, and what changed afterward.
We audited our own legal setup and found 9 risks in 5 minutes.
Before drafting a privacy policy, we audited our own product architecture. Three specialists and two judges surfaced critical gaps in GDPR readiness, cross-border transfers, and Chinese provider disclosure for $0.21.
Standard tier · 3 specialists + 2 judges · 4m 55s · $0.21
You can't trust a single AI to audit your code.
We ran the same production codebase through 9 engines in 4 configurations, then verified every finding against source. The strongest individual model still missed a SQL injection and a four-bug exploit chain.
4 configurations · 9 unique engines · all findings verified · $0.64 total
Passing tests didn't mean it was safe to ship.
74 files, 10 end-to-end tests, all passing. Independent review still found 14 more issues: concurrency bugs, silent failures, and credential exposure risks. Half required a second reviewer to surface.
2 independent reviewers · 17 total issues · 14 fixed same session · under $0.10
The SSRF fix that passed its tests and was still unsafe to ship.
A production SaaS had 7 security findings to patch in one session. The first-pass fixes compiled and tested. Independent review then caught two bugs hiding inside the patches themselves.
2 reviewers · 2 review rounds · 4 files · 14 tunnel-aware test cases · same-day deploy
Our audit pipeline reviewed its own expansion — from inside the editor.
We wired MegaLens into the IDE and ran the first end-to-end test on a real task: our own expansion. It caught 3 of 4 structural risks before code existed. The judge tier then caught 5 more that the front-line reviewers missed, including the one real high-severity defect.
~50k host tokens saved · 3 of 4 risks caught pre-code · 49/49 regression · $0.21