Every AI decision becomes verifiable evidence. Stops unsafe AI actions before execution. What was evaluated. What was decided. What was executed. Tamper-evident. Replayable. Audit-ready.
# Before: action executes with no gate agent.run(tool="delete_record", args={"id": 123}) # After: every action passes through the Evidence Layer result = gate.execute(handle, risk_score=0.95, method="DELETE", path="/records/123") # → DeniedExecution(CONTAIN) # risk 0.95 ≥ threshold 0.90 → action never executed # evidence recorded: hash-linked, tamper-evident
The risk is no longer what a model says. It is what the system does — the API call it makes, the workflow it triggers, the action it takes. By the time an alert fires, the damage is done.
Most AI deployments have no verifiable record of what was decided, why, or what executed. When something goes wrong, there is nothing to replay, audit, or present to regulators.
The Evidence Layer is a structured set of capabilities. Each component is independent, composable, and designed to work together as a single runtime infrastructure layer.
| Capability | SoruvaGuard | Vendor A | Vendor B | Vendor C |
|---|---|---|---|---|
| Inline enforcement gate | ✓ | — | — | — |
| ALLOW / CONTAIN before execution | ✓ | — | — | — |
| Tamper-evident audit chain | ✓ | — | — | — |
| Evidence Bundle per decision | ✓ | — | — | — |
| Chain integrity verification | ✓ | — | — | — |
| Risk scoring (5 dimensions) | ✓ | ✓ | ✓ | — |
| Prompt injection detection | ✓ | ✓ | — | — |
| Observability / monitoring | — | ✓ | ✓ | ✓ |
Runtime enforcement, tamper-evident audit chain, and Evidence Center — live demo walkthrough.