Product
Continuous AI governance, evaluated and enforced at every inference.
EvidentAI is the continuous AI governance layer between your AI agents and your regulators. We map your workflows, record every AI decision, evaluate policy at every inference, and produce audit-grade evidence on demand, so when an examiner asks why the AI said what it said, the answer takes hours, not weeks.
Posture
Setup & configuration governance
Governance starts before the first inference, and it starts from understanding the workflow. EvidentAI holds the workflow as a structured object: the agents in it, the processes and tasks each one runs, and the policy bound to the whole. Configuration is evaluated against that structure: tool scope, model pinning, prompt provenance, guardrail settings, egress destinations.
A posture tool sees that an agent holds a tool. EvidentAI sees which task needs it, inside which workflow, under which policy, and flags the mismatch before ship. Each check is an observation against the same control schema that governs runs, so posture findings and runtime evidence land in one record. A build gate applies the evaluation in CI, and drift detection raises a finding when the running setup diverges from the approved one.
Evaluation
Continuous evaluation
Your AI policies are bound to AI workflows and evaluated in real time — at every inference, not every quarter. EvidentAI's policy engine watches inference traffic continuously and evaluates obligations as they fire.
Drift, regressions, and policy violations surface the moment they occur — with the decision context attached.
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Enforcement
Runtime enforcement
EvidentAI blocks, routes, or requires human sign-off before risky agent actions complete. Enforcement happens in the request path, not after the fact.
Every enforcement decision is itself an evidence event — visible to examiners, attributable to a control, and replayable.
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Security
Vulnerability monitoring
EvidentAI maintains an AI vulnerability catalog with per-tenant occurrences drawn from live findings, ranked by severity. Each vulnerability maps to techniques, so security teams see AI risk in the same language they use for the rest of the estate.
Coverage views show which defenses are in place and which techniques are unmitigated. Every finding feeds the same evidence pipeline as every other control.
Human oversight
Human-in-the-loop enforcement
When policy requires human sign-off, the action stops and lands in the sign-off queue with full decision context attached. Reviewers approve, reject, or escalate; the outcome becomes part of the evidence record.
Oversight is a governed step in the workflow, not a screenshot in a shared drive. Every review is attributable: who decided, when, and what they saw.
Workflows
Workflow-based governance
The unit of governance is the workflow, not the model. Register a credit-decisioning or claims workflow once, and EvidentAI tracks every run: which agents acted, what they saw, which policies fired, where a human signed off.
Observed topology shows the workflow as it actually executes — and the same agent carries different obligations inside credit decisioning than inside customer service.
Evidence
Evidence packages & framework mapping
Findings, runs, policy evaluations, and sign-offs compile into evidence packages built for examiner review. Controls map to the frameworks your assessors already use, including .
Bias cohort monitoring, PII shielding, and DSAR handling produce evidence on the same backbone.
Next step
Ready to see EvidentAI on your own AI workflows?
We're recruiting founding design partners in banking, insurance, and healthcare. Explore the live demo, book a demonstration, or read the technical detail of how the platform works.