AI writes your code.
Qodex catches what breaks.
One autonomous agent that reviews your code and runs API, UI, and security tests against your real app.
AI multiplied the PRs.
Testing hasn't kept up.
LLMs reset what one engineer can ship. QA, code review, and stale test suites are now the bottleneck.
- ~5x
longer PR review time under high AI adoption
- 3x+
increase in the incidents-to-PR ratio
- +31%
more PRs merge without any review
Source · Faros AI Engineering Report 2026
Passing tests isn't the same as working software.
Qodex reads your code and drives your app. Nothing else does both.
Qodex is built on both. It reviews a diff knowing what the feature does in production, tests the app knowing what the code intended, and confirms findings with live probes against the pull request's preview deploy.
One agent runs review, testing, and security from the same scenarios.
main from fix/tenant-billing-isolation+318-9414 filescheckout-api/billing.tsline 84const billing = await db.billing.find(orgId)const billing = await db.billing.find({ orgId, callerOrgId })Tenant isolation is broken here. An Org A admin can read another org’s billing. Scope the query to the caller’s org.
GET /v1/orgs/{orgB}/billing returns 200 for an Org A admin (expected 403). Cross-tenant billing is exposed.
Scenario “Admin cannot access tenant billing across orgs” failed: GET /v1/orgs/{orgB}/billing returned 200 instead of 403.
Qodex / code reviewchanges requestedQodex / security1 criticalQodex / tests1 failed of 41Security semantics are inverted on purpose: a pass means the attack was blocked, so the agent cannot make a failing test go green by relaxing the assertion.
Your incidents become tests, on their own.
Qodex reads the bugs your team already files and turns them into scenarios that run against staging.
writes the scenario
you approve it
Runs on your triggers: on demand, on a schedule, or fired by CI, a deploy hook, or any webhook.
Every failure comes back as one of three things.
That distinction is the difference between a gate your team trusts and a bot your team mutes.
Scenarios are standard Playwright and HTTP code you own and can export. Replays make no model call, so the suite stays cheap as it grows.
Out of people's heads, into one living record.
Qodex keeps your scenarios in one place, owned by the team and proven continuously: the authoritative picture of how your software should behave.
Import what you already have: spreadsheets, OpenAPI specs, Postman collections, existing tests. Qodex keeps it current from there.
| Scenario | Sev | Status |
|---|---|---|
| Expired card is declined cleanly | High | Pass |
| Admin can’t read another org’s billing | Crit | Fail |
| Invite link expires after seven days | Med | Pass |
| Checkout preserves cart after auth refresh | High | Pass |
| Password reset rejects re-used tokens | High | Review |
Teams already trust Qodex with their testing.
“We now detect issues in staging instead of finding them after deployment.”
Verified G2 review
“The no-code interface helps our whole integration team write and manage test cases, and drastically reduces the time spent on QA.”
Verified G2 review
“It lets our small team stay confident in releases without needing a dedicated QA resource.”
Verified G2 review
Questions teams ask before switching.
How is this different from an AI code reviewer or bug bot?
Code reviewers read the diff and guess. Qodex runs your scenarios against the real running app, then shows what actually broke. One reads, the other runs. Try both for a sprint and compare what each one catches.
Does Qodex change our code, merge, or deploy on its own?
No. It posts findings and status checks on your pull requests, and a human decides what merges. When a test goes stale it proposes the repair as a diff for you to approve.
What access does Qodex need, and what happens to our code and data?
The app requests read access to your pull requests, not write access to your source. Data is encrypted in transit and at rest on servers in the United States, isolated per project, never sold, and never used to train models.
How are our credentials handled, and what do model providers see?
Environment tokens are cached for thirty minutes, cleared when you save an environment, and redacted in API responses. Bring your own model key if you prefer; every call is logged, provider agreements exclude training on your data, and cached replays make no model call at all.
What do we own if we leave?
Everything. Scenarios are standard Playwright and HTTP code you can export and run anywhere, with no proprietary runtime.