ClearGate AI - Shadow AI approval enterprise.

Problem Employees often adopt AI tools before governance teams can approve them. Security, privacy, procurement, and GRC teams then need fast answers to practical questions: Which unapproved tools are already in use? Which tools touch source code, call recordings, customer notes, contracts, or internal documents? What public evidence supports an approve, conditional approve, escalate, or block decision? Has the vendor documentation or public risk profile changed since the last review? Manual vendor review is slow because trust centers, privacy policies, subprocessor pages, docs, and public risk signals are scattered across the web and change over time. Solution ClearGate AI turns Shadow AI intake into an evidence-backed approval workflow: Shadow AI Inbox -> Band Agent Room -> Live Public Evidence -> Policy Gate -> Decision -> AI Vendor Passport Memo -> Continuous Re-review The current app opens with a deterministic seeded judge workspace containing 11 AI tools, varied risk levels, and varied decisions. Reviewers can import additional tools, run queue review, run a Band agent review, run live verification for a vendor, inspect evidence rows, override decisions, save reviewer notes, and export approval memos. Continuous re-review is implemented as repeatable reviewer-triggered verification through the queue and vendor review flows. There is no background scheduler or database persistence in this build. Band Agent Room The Agent Room tab coordinates six deterministic demo agents over the selected vendor: Discovery Agent Security Agent Privacy & Legal Agent Finance & Procurement Agent Compliance Agent Policy Gate Agent Running the Band review creates a collaboration timeline, shared context packet, recommendation, audit hash, and memo-ready Band Agent Finding evidence records. Human reviewers can explicitly approve with conditions, escalate, or block from the room; those actions are saved into reviewer notes and included in memo/export payloads.