AI agents are moving into production faster than the controls around them. They are handling customer data, financial transactions, infrastructure operations, and business-critical workflows, often with broad permissions and no hard limits on what they can actually execute. For security and compliance teams, that is a significant and growing exposure.

Faramesh is a runtime enforcement platform for AI agents. Before any agent action executes, Faramesh checks it against your organization's policies. Actions are permitted, blocked, or escalated for human approval in real time, with every decision logged to a tamper-evident audit trail. Your agents operate within defined boundaries, and your team has the evidence to prove it.

Unlike monitoring tools that observe and alert after the fact, Faramesh enforces before execution. The controls are deterministic and policy-driven, not dependent on a second AI making a judgment call. That distinction matters when you are defending a position to a regulator, an auditor, or a board.

Faramesh is open source, deploys in minutes, and works with 13 of the major agent frameworks your engineering teams are already using, including LangGraph, CrewAI, AutoGen, and MCP. Open source and free to start.

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