Edison Watch
Edison Watch is an AI data leak prevention platform that helps organizations increase AI adoption without risk - governing how agents access company data at runtime.
Edison Watch is an AI data leak prevention platform that helps organizations adopt agentic AI - Claude Cowork, Codex, Cursor, ChatGPT, or your own custom agents - without putting company data at risk.
Increase AI adoption without risk. Every team wants more agents; the blocker is governing what those agents can do with company data. Edison governs agent data access at runtime, so security leaders can say yes to AI adoption instead of slowing it down.
How it works
Edison sits between your agents and your company data, assigning a risk score to every agent action. It enforces data security policies at runtime, with agent-architecture awareness (context-window ACLs, subagents, and more) and identity awareness.
Edison can secure agents at the device level, agent level, or data level - so you can roll AI out broadly while keeping data access governed end to end.
Governing agent data access
A common piece of advice for agent security is "don't give your agents write access" - but that's not helpful; agents are only useful when they have autonomy. Instead, we recommend a more nuanced approach:
In a fresh LLM context window, give agents access to all the tools. As they access more and more sensitive information, restrict the access the agents have to other tools.
For example, an agent that has only read public information can use any write tool it wants, autonomously, without any approval. An agent that has read sensitive company financial data, on the other hand, should have restricted access to write tools that could potentially exfiltrate that data.
The more sensitive the data an agent has seen, the tighter its ability to send data out - and Edison enforces exactly that, automatically, on every action.
Core Features
- Agent Architecture & Identity-Aware Runtime Enforcement - Risk-score and enforce policy on every agent action at runtime, aware of context windows, subagents, and the identity behind the agent.
- Multi-Device Agent Data Security - Secure agents wherever they run: on device, at the agent, or at the data layer.
- Automatic Shadow MCP Quarantine - Detect new connectors (e.g. ChatGPT Apps) added to AI apps and quarantine them until an admin approves.
- Connector Supply Chain Security - Pin and vet the connectors your agents depend on, so a compromised dependency can't reach your data.
Get Started
Getting Started
Connect your first agent and see governed data access in minutes.
User Guide
What you see as an end user - connectors, sessions, and security flags.
Admin Guide
Manage users, roles, policies, and connector configurations.