Quality · Autonomous verification

Tests that prove what software actually does

We reconstruct a system's real behaviour from its source, then generate end-to-end tests that run against it. A second, independent check verifies the first before anything ships.

Static analysisMulti-agent groundingTest generationQuality
Claimdrafted by agentSourcefile · line · ownerIndependent checkre-reads the source
The challenge

Test coverage was thin in exactly the places that mattered, and writing it by hand never kept pace with the code. The hard part was never generation, it was grounding: making sure a generated test reflects what the system truly does.

What we built
  • Static analysis across languages that reconstructs real call chains, from entry point to database, queue, and file.
  • A labelling agent that describes each feature, and a second, independent agent that re-reads the code and verifies the description before it is trusted.
  • Generated tests that run against the live system and record a verdict, with no model in the loop at execution time.
The outcome
  • Fabricated claims are caught by the independent check before they reach a test.
  • Coverage tracks the code instead of trailing it.
  • Every generated test is grounded in a real route, table, and assertion.
FAQ

Common questions

Grounding, not generation, is the hard part. We reconstruct real call chains from the source with static analysis, then a second independent agent re-reads the code and verifies each feature description before it is trusted. Fabricated claims are caught before they ever reach a test.

No. Models help generate and verify tests, but at execution time there is no model in the loop. Generated tests run against the live system and record a plain verdict, so test results stay deterministic and reproducible rather than depending on a model's mood.

Because tests are derived from the system's reconstructed behaviour rather than written by hand, coverage tracks the code instead of trailing it. When call chains change, the analysis picks it up, so the thin spots that usually matter most stop being left behind.

One agent describes a feature; a second, independent agent re-derives that description from the code and must agree before it is used. This adversarial step is the main defence against confidently wrong tests, the failure mode that makes automated test generation untrustworthy.

Have a problem shaped like this?

If this looks like the kind of system you need, let's talk through it. First call is always free.

Start a project→