AGEI turns AI lifecycle events, policy decisions, human approvals, agent actions, and audit requests into tamper-evident evidence that can be verified, reviewed, and exported.
AGEI is an evidence infrastructure layer that captures governed AI activity as cryptographically verifiable receipts. It applies policy gates at consequential lifecycle points, records human review decisions as auditable evidence, monitors agent actions before execution, and materializes audit-ready bundles when proof is required.
AGEI is not another AI monitoring dashboard. It is an operational governance system that preserves evidence of what happened, why it happened, under what authority, and whether controls fired.
Organizations write AI policies, model review procedures, and approval workflows. But when critical moments occur—a model deployment, an agent tool call, a high-risk decision—the question remains:
Can you prove the control actually executed?
AGEI creates tamper-evident evidence that governance controls fired, policies were evaluated, human reviewers made decisions under appropriate authority, and agent actions were authorized—or denied—according to organizational rules.
Five integrated capabilities that turn AI operations into governed evidence
Convert governance policies into enforceable decision points.
Turn human review, approval, denial, and escalation into governed evidence.
Capture agent actions, tool calls, delegation, privilege, and policy outcomes.
Materialize lightweight evidence into regulator-, auditor-, or incident-ready bundles.
Record what happened, why it happened, under what authority, and whether controls fired.
AI Event
Policy Gate
Human Review
Evidence Receipt
Audit Pack
Implement and enforce policy controls across AI systems
Access verifiable evidence trails for AI operations
Document model lifecycle governance and approval workflows
Preserve evidence needed for regulatory review
Monitor agent privileges and detect unauthorized actions
Support litigation and incident investigation with proof
Integrate governance into MLOps and LLMOps workflows
Quantify governance controls and evidence coverage
Claims agent attempts to issue a $425 refund. AGEI captures agent ID, session, tool call, and risk level.
Pre-action gate evaluates against refund policy. High-value refunds trigger escalation outcome.
Supervisor receives notification. Reviews request. Approves refund with justification.
AGEI records: (1) Agent request receipt, (2) Gate evaluation receipt, (3) Human decision receipt, (4) Action authorization receipt.
Six months later, auditor requests all high-value refunds. AGEI materializes audit pack with all linked receipts, verified hashes, and policy context.
View detailed feature documentation, explore code examples, or request access to the platform.