Before the agent acts, CAVRA decides.
The runtime authority layer for AI agents.
CAVRA governs AI-agent actions at the moment of risk: before code changes, shell commands, Git operations, MCP tool calls, CI/CD workflows, cloud operations, or infrastructure changes execute.
- Pre-action
- Decisions before execution
- Evidence
- Signed records and audit packets
- AISPM
- Runtime activity becomes posture
The category problem
AI agents are becoming operators. Your controls are still spectators.
CAVRA sits between agent intent and action. It evaluates policy, trust context, approval requirements, and evidence obligations before risky work touches code, cloud, identity, repositories, or production workflows.
What CAVRA does
Decide, enforce, prove, and assure.
Decide
Evaluate agent actions before execution using policy, context, and trust state.
Enforce
Allow, block, require approval, shadow, or attest based on risk and environment.
Prove
Generate signed evidence, audit records, control mappings, and reviewer context.
Assure
Convert runtime evidence into AISPM posture, findings, blockers, and reports.
Interactive Decision Simulator
Watch CAVRA evaluate an agent action.
Select an agent scenario and see the policy decision, evidence packet, and AISPM posture signal update together.
AI Security Posture Management
CAVRA does not only discover risk. It creates control evidence at the moment of action.
Product paths
One product model. Four clear paths.
CAVRA Community
Full self-hosted runtime governance product and public codebase.
Deploy CommunityCAVRA Managed
Hosted tenant operations, live ingestion, reports, audit storage, upgrades, and support workflows.
Explore ManagedEnterprise Subscription
Commercial support, SLA, certified connectors, policy/compliance packs, and implementation help.
Talk to UsTrial Access
Time-limited evaluator path for one guided proof-of-value use case.
Request TrialCAVRA Managed
Managed CAVRA, operated for teams that need production trust without operating every backing service.
What we operate
Tenant onboarding, policy registry, dashboards, report delivery, audit storage, monitoring, upgrades, support handoff, and billing operations.
Deployment models
Managed, self-hosted Community with Enterprise Subscription, or hybrid where sensitive data remains customer-side.
Data handling
Evidence, connector metadata, retention, export, deletion, and tenant isolation are explicit operating boundaries.
Enterprise Subscription
Commercial support for serious AI-agent governance.
Support & SLA
Response targets, escalation, upgrade guidance, and release review.
Certified Connectors
GitHub, GitLab, Azure DevOps, SIEM, ITSM, ChatOps, cloud, and report providers.
Policy Packs
AI coding-agent controls, MCP trust, CI/CD, IaC, regulated release, and evidence readiness.
Compliance Packs
NIST AI RMF and OWASP GenAI/LLM risk mappings, plus audit evidence templates.
Implementation Services
Tenant design, policy design, connector setup, pilot launch, and readiness review.
Procurement Pack
Security questionnaire answers, architecture brief, data-handling brief, and trust docs.
Evidence Packet Explorer
Different readers, one control record.
Trust Center Preview
Built for security teams who ask where the data, credentials, and evidence live.
Choose your path
Different teams see different proof.
Resources
Buyer packet shelf.
Put an authority layer between AI agents and action.