AI Admissibility
Built this around one simple idea: the workflow that wants to execute should not be the same place that decides whether execution may continue. This project puts an external allow/deny boundary before action. Public entry points: * live pilot * commercial request * private deployment There is also a GitHub Marketplace action install surface, but the main point is the boundary model itself: decision stays outside the workflow that is asking to proceed. Looking for feedback from people working on CI/CD, security controls, approval boundaries, and automated execution.
AI Admissibility launched on April 24, 2026 with 3 votes, #2,709 of 21,248 launches that month and more than 50% of that year's launches.
What it does
AI Admissibility places an external allow or deny boundary before automated execution continues. Instead of relying only on post-event scanning or self-approval inside the same workflow, it moves the decision boundary outside the workflow that is asking to proceed. Public paths today include a live pilot, a commercial request path, and a private deployment path.
AI Admissibility is an external pre-execution admission boundary for high-impact automated action. No Admission = No Execution.
Scanners are too late. Control automated and AI-driven execution before action. Hosted Authority Pilot places an external allow/deny boundary between intent and execution, so the decision stays outside the workflow that is asking to proceed. There are three practical paths: commercial request, live pilot, or private deployment. Commercial access stays on the main request path. The pilot remains a separate live evaluation path for testing the boundary before action. AI Admissibility decides before execution whether an AI-driven action is admissible. No valid boundary context means no admissible execution. Organizations already running AI-driven or automated workflows where actions do not…from ai-admissibility.com
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