Auditable & legible
Every run is recorded as a step-by-step trace of what the AI did and why — so you can review, explain, and, if needed, stop it instantly.
The concept, in plain terms
Trust in an autonomous system requires being able to see what it did. Legibility means each run produces a readable, step-by-step trace — the reasoning, the sources, the actions — not a black box. Auditability means those events are recorded so you can review and explain any decision after the fact.
And when something looks wrong, a two-level kill switch stops a run immediately — gracefully, or hard.
From concept to capability
Per-run trace
Each run records what it did and why, step by step.
Learn moreAudit events
Actions are logged for review and compliance.
Learn moreTwo-level kill switch
Stop any run instantly — a graceful stop or a hard halt.
Learn moreVerifiable answers
Outputs trace back to their sources.
Learn moreWhat you get from it
- Explain any decision after the fact.
- Catch and stop problems immediately.
- The transparency auditors and security teams expect.
More on security & trust
Multi-tenant isolation by design
Every organization is isolated. Data, knowledge bases, and agent personas are scoped per tenant, with fail-closed access checks so a new or anonymous caller can never see another tenant’s data.
Learn moreHuman-in-the-loop control
Outward actions — writing files, running commands, calling integrations — pause at an approval gate until a human signs off. Autonomous mode is opt-in, never the default.
Learn moreSSO & identity
Sign in with your identity provider via OAuth, including Google and Microsoft Entra. Sessions use short-lived tokens with proactive refresh.
Learn moreSee auditable & legible on your own data
Book a walkthrough and we'll show this working against the systems and use cases that matter to you.