Precedent

Precedent is a governance harness that lets company AI agents act, learn and be stopped, safely. Agents in companies fail in two ways: they do things they shouldn’t (install a web-search MCP that reads prompt-injected pages, query restricted data) and they forget what people taught them (every agent re-guesses the same undocumented warehouse table). In Precedent, the model only proposes; a deterministic policy engine decides every tool and MCP call before anything runs. Web-search MCPs are blocked outright (Claude judges, policy decides). Other MCPs become InfoSec requests ranked by how many people asked, with Raindrop evidence and a recommendation. When a user corrects an agent, a policy checkpoint runs and a human approves saving that lesson to MongoDB Atlas for their department, so the next engineer’s agent gets it right on the first try while other departments never see it. Precedent also drafts its own guardrails from repeated human approvals, replays them against recorded history, and has Raindrop verify the runs behind them before they ship. One click quarantines a compromised connector for every agent. The demo runs the same prompt side by side, without Precedent and with it. https://drive.google.com/drive/folders/1XlgovvrrhaZ9RycRNUXshxOfaGezh8Ch?usp=sharing