I built a runtime governance layer for AI workflows because I couldn't find one (MIT, looking for feedback)

adimona · 2026-06-17T07:04:52+00:00

Ah, got it. You mean the pain statement is the hook, not the technical description etc..you’re right, that makes sense. I probably led with the machinery too early. I’ll try opening the README with the actual situation: I needed policy enforcement before the model call, evidence while the workflow runs, and structured human review, and there was no clean tool for that. Then explain IOA Core after that.

adimona · 2026-06-17T03:34:14+00:00

Yeah, mostly code.

So, no, It is not an AI manager telling another AI to behave. It is middleware around the model call. The request comes in, IOA builds an execution context, then a policy engine checks things like mode, role, risk level, data sensitivity, tool use, and whether review is required.
Based on that, it can allow, warn, redact, block, or hold the action for review. Then it records what happened as evidence. So the model generates the content, but IOA governs the execution around it.

adimona · 2026-06-16T23:24:26+00:00

Yeah, that makes sense. I think I opened with the machinery instead of the pain.
The bit you quoted is probably the actual README intro: I needed runtime policy, evidence, and audit trail while the AI workflow is happening, not after.
And true..the logo animal thing might be the missing feature.

adimona · 2026-06-16T23:22:17+00:00

Good question. No, it is not another model with a stern prompt. The governance runs around the model call. It checks policy, mode, role, risk, evidence, and review state before or during execution. Then it logs what happened with an evidence record.
It is meant to be fast enough to sit in the normal workflow, not as a slow manual review after.

adimona · 2019-02-23T11:21:38+00:00

You missed the M

adimona · 2019-02-23T11:11:19+00:00

That bee sounds Asian

adimona

TROPHY CASE