AI Use Cases
- · AI-governance-shaped intake form (post-cleanup)
- · Filesystem store: data/projects/{org_id}/{case_id}/
- · Qdrant per-case collections · hybrid (BM25 + vector) search
- · Workflow runs link back to a case for traceability
A multi-tenant AI governance + multi-agent orchestration platform with compliance-by-construction: every AI call passes a policy gate, lands in a hash-chained audit log, and exports as a signed Evidence Pack. Ships in four deployment shapes (cloud-only · cloud+tray · cloud+daemon · local-MCP) — see below.
One codebase, four deployment topologies. Each mode is real today — the daemon binary, the tray app, and the cloud are all one repo.
All execution server-side. Tool runtime = LocalToolRuntime in the cloud process. Fastest path to demo.
Tray pops native HITL approval dialogs when cp.tool.hitl fires; auto-approve gate uses precedent engine. Cross-instance reconcile via cp.hitl.resolve.
Cloud → user machine: 7 local tools (read/write/edit/bash/glob/grep/list) routed via RemoteToolRuntime. Pairing code → device token bound to caller's org.
Same daemon binary, mcp role. Tools exposed as MCP. No governance overlay in this mode — pure tool execution. Set CP_VENDOR=claude_desktop / codex_desktop for vendor tagging.
One LLM call traverses all 7 gates. Failure at any gate is itself audited.