How should teams audit AI agents before they act?

AI agents are moving from chat to action — sending emails, posting to Slack, sharing files, updating records. The problem: once an agent can act, you can't ship it without answering three questions — what's it allowed to do, what did it actually do, and can you prove the log wasn't edited?

AgentBlackBox is the governance and accountability control plane for AI agents — approvals, policies, audit evidence, identity lifecycle, and compliance in one system.

🛡️ Policy gate on every action — allow / redact / require-approval / deny. Default-deny, fail-closed.

✋ Human-in-the-loop approvals with segregation of duties (you can't approve your own action).

🤖 Agent identity & governed tools — register agents, scope their tools, ordered activity timelines.

🔗 No-bypass connector control for Slack, Gmail, Drive, GitHub, Notion — credentials stay vaulted (optional setup).

🧾 Tamper-evident audit — hash-chained events → signed checkpoints → optional Bitcoin anchoring. Independently verifiable, with signed exports.

🪪 Enterprise-ready — SSO, SCIM provisioning, tenant isolation, RBAC, retention, legal hold, DSAR, SIEM integration (optional configuration; SSO enforcement & SIEM streaming off by default).

🟢 Safe by default — off until you opt in; rolls out shadow → enforce, reversibly.

It's multi-tenant, role-based, and API-first — a production SaaS, with every guarantee covered by an automated verification suite.