Statistical process control for AI systems.
The LLM is a sensor, not a judge. The model turns messy reality into typed claims that carry their evidence. Deterministic code verifies those claims, makes every decision and computes every number. Humans approve anything that acts.
Seismograph runs the same question at an AI system many times instead of once, and watches how much the answers move.
A control chart, the same tool a factory uses to spot a machine drifting out of tolerance, turns that movement into a signal rather than an opinion.
When a model update or a prompt edit quietly changes behaviour, the chart says so before your users do.
There is no web application here. Every endpoint below is JSON, and both reads and writes
require a bearer token; unauthenticated requests are refused with 401. The
interactive schema at /docs is deliberately public so the route map can be
read without credentials.
| method | path | what it does |
|---|---|---|
| POST | /api/v1/contracts | register a behavioural contract |
| POST | /api/v1/runs | execute the plan, store metrics, decide the gate |
| GET | /api/v1/reports/{contract} | metrics history and gate decisions |
version 0.3.2 · commit 400667d ·
built 2026-08-03T02:38:25Z · environment production
Values are baked from build arguments. unknown means the image was built without
them, which is reported rather than replaced with a plausible-looking string.