Prefactor

About Prefactor

Prefactor is the definitive control plane for AI agents, engineered to transform autonomous systems from experimental proofs-of-concept into governed, production-ready assets. It addresses the critical governance gap that emerges when AI agents transition from demos to real-world deployment, particularly within regulated enterprises. The platform provides every AI agent with a first-class, auditable identity, bringing the rigorous principles of human identity and access management to the autonomous software layer. By offering dynamic client registration, delegated access, and fine-grained policy controls, Prefactor creates a single, elegant layer of trust. It enables security, product, engineering, and compliance teams to align around a unified source of truth, offering shared visibility, control, and auditability. Built with scalability and stringent compliance in mind, it delivers SOC 2-ready security, human-delegated oversight, and interoperable OAuth/OIDC support, empowering SaaS companies and enterprises in sectors like finance, healthcare, and mining to deploy AI agents with confidence and operational integrity.

Features of Prefactor

Identity-First Agent Governance

Prefactor assigns a unique, first-class identity to every AI agent, ensuring each action is authenticated and every permission is explicitly scoped. This foundational feature moves beyond basic API keys to implement dynamic client registration and delegated access controls, applying proven human identity governance frameworks to autonomous systems for unparalleled security and management.

Real-Time Agent Monitoring & Dashboard

Gain complete operational visibility across your entire agent infrastructure from a centralized dashboard. Monitor all agents in real-time to see which are active, idle, or failing; track the resources they are accessing; and identify emerging issues before they cascade into production incidents, providing teams with immediate situational awareness.

Compliance-Ready Audit Trails

Our audit logs translate technical agent actions into clear business context, creating narratives that stakeholders and auditors understand. Instead of cryptic API calls, you get answers to "what did the agent do and why?" This enables the generation of audit-ready reports in minutes, designed to withstand regulatory scrutiny in highly regulated industries.

Policy-as-Code & Automated Permissions

Manage and enforce agent access through declarative policy-as-code, allowing for precise, fine-grained role and attribute-based controls. Integrate these policies directly into your CI/CD pipeline to automate permissioning, ensuring governance scales seamlessly with development velocity and deployment frequency.

Use Cases of Prefactor

Scaling AI Agents in Regulated Enterprises

For financial services, healthcare, or mining companies, Prefactor provides the governance foundation required for production deployment. It solves the critical compliance blocker by delivering the audit trails, real-time visibility, and identity controls that internal security and regulatory teams demand to approve agent-based applications.

Unifying Multi-Framework Agent Operations

Teams using a mix of AI agent frameworks like LangChain, CrewAI, or AutoGen can integrate Prefactor to bring all agents under a single control plane. This eliminates fragmented governance, providing consistent monitoring, identity management, and cost tracking across diverse tools and custom builds.

Implementing Model Context Protocol (MCP) at Scale

As MCP becomes the standard for agent-tool integration, Prefactor offers the essential production control layer it lacks. Organizations can deploy MCP-enabled agents with full visibility, auditable access to tools and data, and emergency kill switches, moving from experimental adoption to governed implementation.

Agent Cost Optimization and Analysis

Beyond security, Prefactor provides detailed cost tracking across different cloud providers and agent instances. Teams can identify expensive execution patterns, optimize resource utilization, and attribute spending accurately, turning agent operations from a black-box cost center into a managed, efficient investment.

Frequently Asked Questions

What is an AI Agent Control Plane?

An AI Agent Control Plane is a centralized governance platform that provides identity, security, observability, and compliance for autonomous AI systems. Think of it as the management layer that brings operational control, auditability, and human oversight to software that acts independently, ensuring it aligns with business and security policies.

How does Prefactor handle compliance for regulated industries?

Prefactor is architecturally designed for regulated environments. It provides immutable, business-contextual audit trails, SOC 2-ready security controls, fine-grained access policies, and human-delegated authorization. These features allow you to demonstrate exactly what agents are doing, satisfy auditor inquiries, and maintain a verifiable chain of custody for all autonomous actions.

Can Prefactor work with any AI agent framework?

Yes, Prefactor is built for interoperability. It offers seamless integration with popular frameworks like LangChain, CrewAI, and AutoGen, as well as support for custom agent implementations. Its standards-based OAuth/OIDC support and flexible architecture allow it to be deployed into diverse tech stacks within hours.

What is the difference between Prefactor and using standard API keys?

Standard API keys (M2M tokens) provide basic authentication but lack identity context, granular delegation, real-time visibility, and comprehensible audit trails. Prefactor elevates this by giving each agent a unique, revocable identity with scoped permissions, full session monitoring, and audit logs that explain agent behavior in business terms, which is essential for production and compliance.