Signed AI Agent Governance
Agents register with real Ed25519 identity and sign governed actions before Sentinel evaluates them.
How Sentinel worksLearn Sentinel SCA
Sentinel SCA governs AI actions before execution. It combines signed agent identity, tenant dashboards, RBAC, evidence exports, billing entitlements, Ops safety controls, and tamper-evident audit trails into one governance operating system.
What Customers Are Buying
Customers are not only buying API calls. They are buying governed execution: Ed25519-signed agents, organization-scoped controls, decision evidence, audit packages, user roles, subscription enforcement, and protocol safety.
Tenant Evidence
Each organization gets scoped audit timelines, decision exports, and evidence ZIP packages.
See packagesRBAC and Controls
Owners, admins, auditors, and viewers get role-appropriate access to dashboards, audit, agents, billing, and exports.
Customer portalOps-Backed Safety
Sentinel Ops monitors billing state, risk, runtime health, audit-chain integrity, and Global Protocol Freeze.
Read architectureValidate AI Requests Before Execution
Learn how to prevent unsafe autonomous actions before they become real.
Read articleAgri-Nexus Prime Case Study
See how Sentinel governs agricultural telemetry, fan-control proposals, execution boundaries, receipts, and audit evidence.
Read case studyCLARA — Design Partner & Reference Integration
Status: Shadow governance. Sentinel evaluates proposed CLARA actions but does not currently block CLARA execution. Not presented as a customer deployment.
See how Sentinel adds independent shadow governance to an external autonomous agent system before selective enforcement.
Read case studyComprehensive Validation
Review governance correctness, signatures, replay, concurrency, reputation, review timeouts, and evidence export results.
Read validation summarySentinel governance flow
Customer Agent -> Ed25519 Signature Verification -> Tenant + Capability + Schema Checks -> Risk + Policy Evaluation -> ALLOW / REVIEW / DENY -> Tenant Audit Timeline -> Evidence Export -> Ops Runtime Oversight
AI agent governance, from policy to execution
Explore the controls behind consequential agent execution: authorization, runtime policy, control planes, approval, audit evidence, MCP tool governance and fail-closed enforcement.
AI Agent Governance
How governance changes when AI systems can take consequential actions.
Read guideAI Agent Control Plane
Identity, policy, authority and evidence around production agent execution.
Read guideAI Agent Authorization
Per-action authority, capabilities, freshness, revocation and execution checks.
Read guideRuntime Policy Enforcement
Deterministic policy decisions applied when an agent is about to act.
Read guideAI Agent Audit Trail
Governance records, signed evidence, integrity and execution-proof boundaries.
Read guideAI Agent Approval Workflows
Human review for bounded consequential actions without approving every step.
Read guideMCP Governance
Authorization and execution-boundary controls for consequential agent tool calls.
Read guideFail-Closed Agent Governance
Why missing, expired or invalid authority must not become permission.
Read guide