Permit0 provides a pre‑execution authorization layer for AI agents, intercepting each action and evaluating it against a deterministic policy framework with built‑in risk scores and compliance mappings across 21 domains.
Funding
Funding not disclosed
Founders
Product
Problem
AI agents often execute actions directly based on their internal decisions, which can lead to unintended financial transactions, regulatory violations, or other high‑risk operations when deployed in production environments.
Solution
Permit0 offers a pre‑execution authorization layer that intercepts every action an AI agent attempts to perform and evaluates it against a deterministic policy framework. The platform provides a canonical taxonomy of agent actions across 21 domains, along with default risk scores and compliance mappings that can be customized by engineering teams. By integrating with existing services such as Stripe, Permit0 can automatically score operations like refunds, allowing high‑risk actions to be blocked or escalated for human review before they are executed. The solution works as a lightweight decorator or middleware, fitting into popular agent stacks (e.g., LangChain, CrewAI, OpenAI Agents SDK) without requiring changes to the underlying model logic. This enables teams to ship AI agents with built‑in financial and regulatory safeguards while maintaining real‑time decision making.
Target Audience
Primary customers are engineering teams in fintech, insurtech, and healthtech organizations that develop and deploy AI agents handling financial or regulated actions.
Features
- Canonical taxonomy covering 21 action domains with built‑in risk defaults and compliance mappings
- Real‑time policy enforcement that scores and blocks actions before execution
- Simple integration via decorator or middleware, compatible with major agent frameworks (LangChain, CrewAI, OpenAI Agents SDK, Claude, etc.)
- Service adapters (e.g., Stripe) that automatically evaluate financial operations such as refunds
- Configurable escalation paths that route high‑risk actions to human reviewers based on risk thresholds
- Deterministic policy engine ensuring consistent decision outcomes across deployments