AI Agent Control Dashboard

When running multiple AI agents, it's hard to audit what they're doing, approve actions, and prevent data leaks. This local-first control plane lets teams see agent behavior in real-time, approve sensitive actions, and keep PII out of logs. Target: enterprises using AI agents.

Multi-agent orchestration is exploding right now — LangChain, AutoGen, and CrewAI all crossed meaningful adoption thresholds in the past year, and enterprise teams are deploying agents into production workflows faster than their security and compliance functions can keep up. No clear incumbent owns the observability and human-in-the-loop control layer specifically; LangSmith touches tracing but isn't built around approval workflows or PII redaction. The $2k–10k/mo revenue band is realistic for a tool sold to a single enterprise team, though it implies landing mid-market rather than Fortune 500, where procurement cycles would demand a much higher ACV to be worth the effort. The most likely failure mode is timing dependency: if the major orchestration frameworks (LangChain, OpenAI's emerging agent APIs) build native control planes, the standalone tool gets commoditized before it can establish sticky contracts.