Stacksona
The approval layer between AI agents and real actions.
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Stacksona - The approval layer between AI agents and real actions.

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Most AI governance tools monitor what agents did after the fact. Stacksona governs actions before they happen. It can pause sensitive agent workflows, apply organization rules, route decisions to a human, and return an approve, modify, or reject response. Every policy check, review, and action is stored in a durable audit trail. It works with any agent that can call an API.

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I started building Stacksona after spending a bunch of time on AI agents and hitting the same wall every time: the agent could actually do the work, but there was no good way to pause it before a risky action, pull a human in, and then let it keep going. Originally I was just trying to solve that one approval step. But once I got into it, I realized approvals were just the tip of it. You also need rules for what triggers a review, notifications, requests that don't just disappear if nobody responds right away, and a real record of what the agent tried, what the reviewer decided, and what happened after. That's basically what Stacksona turned into: infrastructure for human review and runtime governance on top of any agent workflow, so you're not rebuilding all of this yourself every time. I think agents actually get more useful, not less, when there's a human in the loop. This is my attempt to make that easy to bolt on.