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The governance and accountability control plane for AI agents approvals, policies, audit evidence, identity lifecycle, and compliance in one system. Gate risky actions with policy + human approval, and prove what your agents did. control plane for AI agents approvals, policies, audit evidence, identity lifecycle, and compliance in one system.
Hey hunters 👋 maker here.
We kept hitting the same wall everyone shipping AI agents hits: the second the agent can take a real action, security and compliance want a policy gate, a human checkpoint, and a log they can actually prove. We couldn't find one we'd trust, so we built it.
AgentBlackBox sits between your agents and the systems they touch. Actions go through a policy gate (allow/redact/approve/deny, fail-closed), risky ones pause for a human, and every step is hash-chained and verifiable optionally anchored to Bitcoin so even we can't quietly rewrite history. For connector writes (Slack/Gmail/Drive/GitHub/Notion) we're the only execution path; credentials never leave the vault. For enterprises there's SSO, SCIM provisioning, retention/legal-hold/DSAR, and SIEM integration all optional and off by default.
It's off by default and ramps shadow → enforce per team, so trying it can't break your agent.
We're opening 14-day pilots if you're putting an action-taking agent into production (especially anywhere audit-sensitive), I'd love to set you up and hear what's missing. Connect one agent, start in shadow, and review the policy decisions and verifiable trail together. What's the scariest thing your agent could do unsupervised? 👇
Live demo: https://agent-blackbox-five.verc... · Request a pilot: https://agent-blackbox-five.verc...
the audit evidence framing is really thoughtful, treating governance as something you can actually produce rather than just configure
How does the human approval step actually work in practice, like do approvals come through Slack or email or a custom dashboard, and what happens if no one is around to approve a time sensitive agent action?
How does the human approval flow actually work in practice, like is it a Slack message, an email, or something custom, and can you route different policies to different approvers based on risk level?
About AgentBlackBox on Product Hunt
“The flight recorder for AI agents”
AgentBlackBox was submitted on Product Hunt and earned 0 upvotes and 4 comments, placing #141 on the daily leaderboard. The governance and accountability control plane for AI agents approvals, policies, audit evidence, identity lifecycle, and compliance in one system. Gate risky actions with policy + human approval, and prove what your agents did. control plane for AI agents approvals, policies, audit evidence, identity lifecycle, and compliance in one system.
AgentBlackBox was featured in Developer Tools (515.9k followers), Artificial Intelligence (473.7k followers) and Security (2.8k followers) on Product Hunt. Together, these topics include over 188.3k products, making this a competitive space to launch in.
Who hunted AgentBlackBox?
AgentBlackBox was hunted by Sontosh Bhandari. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
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Sontosh Bhandari