Prefactor

About Prefactor

Prefactor is the essential control plane for AI agents, empowering organizations to transition from experimental proofs-of-concept to secure, governed, and scalable production deployments. It solves the critical governance gap that emerges when autonomous AI agents move beyond demos and into real-world operations, especially within regulated industries like finance, healthcare, and mining. Prefactor provides every AI agent with a first-class, auditable identity, bringing the same rigorous principles of identity and access management that work for human users to the world of autonomous software. It is built for product, engineering, security, and compliance teams who need shared visibility and control over their agent ecosystems. By offering real-time monitoring, compliance-ready audit trails, fine-grained policy controls, and enterprise-grade security, Prefactor transforms complex agent authentication and governance into a single, elegant layer of trust. This allows companies to innovate with confidence, accelerate time-to-production, and finally answer the critical question: "What are our agents doing, and do we have control?"

Features of Prefactor

Real-Time Agent Monitoring & Dashboard

Gain complete operational visibility across your entire agent infrastructure from a centralized dashboard. See every agent action as it happens, track which agents are active and idle, monitor the resources they are accessing, and identify emerging issues before they cascade into full-blown incidents. This real-time oversight is the foundation for reliable, production-scale agent operations.

Identity-First Control & Policy-as-Code

Assign every AI agent a unique, first-class identity with delegated access and fine-grained role and attribute controls. Manage permissions through policy-as-code, enabling you to automate security and compliance directly within your CI/CD pipeline. This ensures every agent action is authenticated and every permission is precisely scoped, just like for human users.

Business-Ready Audit Trails & Compliance Reporting

Move beyond cryptic API logs. Prefactor's audit trails translate technical agent actions into clear business context, providing answers that satisfy both engineers and compliance officers. Generate audit-ready reports in minutes to demonstrate exactly what your agents did and why, built to withstand regulatory scrutiny in highly regulated industries.

Enterprise-Grade Security & Integration

Built with scalability and compliance as a core tenet, Prefactor delivers SOC 2-ready security, human-delegated emergency controls, and interoperable OAuth/OIDC support. It works seamlessly with popular agent frameworks like LangChain, CrewAI, and AutoGen, allowing you to deploy a robust governance layer in hours, not months.

Use Cases of Prefactor

Scaling AI Agents in Regulated Enterprises

For financial services, healthcare, or mining companies, Prefactor provides the governance foundation required for compliance approval. It answers critical audit questions, provides real-time oversight of agent activity, and enforces strict access policies, enabling the secure transition of agent pilots into approved, production-grade systems.

Unifying Visibility Across Multiple Agent Pilots

Product and engineering teams running numerous, siloed agent experiments can use Prefactor as a single source of truth. Align security, product, and engineering with shared visibility into all agent activity, cost tracking, and performance, preventing chaos and enabling coordinated, strategic scaling of successful pilots.

Implementing Production-Ready MCP (Model Context Protocol)

For teams adopting MCP as the standard for agent-tool integration, Prefactor solves the "flying blind" problem in production. It adds the essential layer of identity, audit, and control to MCP servers and clients, ensuring this powerful protocol can be used safely and accountably in enterprise environments.

Cost Optimization and Operational Control

Track and analyze compute costs across all your AI agents and providers from one dashboard. Identify expensive or inefficient agent patterns, right-size resources, and implement governance to prevent cost overruns. Gain emergency kill-switch capabilities to immediately halt any agent exhibiting unexpected behavior.

Frequently Asked Questions

What is an AI Agent Control Plane?

An AI Agent Control Plane is a centralized governance layer that provides identity, security, observability, and compliance for autonomous AI agents. Just as Kubernetes is a control plane for containers, Prefactor is a control plane for agents, managing their permissions, monitoring their actions, and ensuring they operate within defined business and security policies.

How does Prefactor handle compliance for regulated industries?

Prefactor is architecturally designed for regulated environments. It creates immutable, business-contextual audit trails that clearly log every agent decision and action. With features like policy-as-code, fine-grained access controls, and SOC 2-ready infrastructure, it provides the evidence and controls needed to satisfy internal compliance and external regulators.

Can Prefactor work with any AI agent framework?

Yes, Prefactor is built to be framework-agnostic. It offers seamless integration with leading frameworks like LangChain, CrewAI, and AutoGen, as well as custom-built agent systems. Its interoperable OAuth/OIDC support and flexible architecture allow it to layer governance onto virtually any agent implementation.

What is the difference between MCP and Prefactor?

MCP (Model Context Protocol) is a standard protocol that allows AI agents to connect to external tools and data sources. Prefactor is a control plane that governs how those connections are made and used. It adds the critical production layers that MCP itself does not provide: identity, authentication, audit logging, real-time monitoring, and security policy enforcement for agents using MCP.