Prefactor

About Prefactor

Prefactor is the essential control plane for AI agents, designed to solve the critical governance gap that emerges when moving autonomous agents from proof-of-concept to production. It provides a centralized platform for managing the identity, access, and actions of AI agents at scale. At its core, Prefactor gives every AI agent a first-class, auditable identity, enabling fine-grained control over what agents can do and clear visibility into what they have done. This is built for product and engineering teams within regulated enterprises—such as banking, healthcare, and mining—where compliance, security, and operational oversight are non-negotiable. The platform transforms complex agent authentication and authorization into a single, elegant layer of trust, allowing companies to align security, product, engineering, and compliance teams around one source of truth. By offering SOC 2–ready security, human-delegated control, and interoperable OAuth/OIDC support, Prefactor removes the biggest blockers to agent deployment: lack of visibility, inadequate audit trails, and uncontrolled access.

Features of Prefactor

Identity-First Agent Control

Prefactor assigns a unique, first-class identity to every AI agent, similar to how human users are managed in enterprise systems. This foundational feature ensures every agent action is authenticated and every permission is explicitly scoped. It enables dynamic client registration and delegated access, allowing teams to manage agent permissions through policy-as-code and automate them within CI/CD pipelines. This identity layer is the bedrock for all subsequent governance and compliance.

Real-Time Agent Monitoring & Dashboard

Gain complete operational visibility across your entire agent infrastructure from a centralized dashboard. This feature allows you to monitor all agents in one place, seeing which are active, idle, or encountering issues in real-time. You can track what resources agents are accessing and identify emerging problems before they cascade into full-blown incidents, providing teams with the situational awareness needed for reliable production deployments.

Compliance-Ready Audit Trails

Prefactor's audit logs are designed for regulatory scrutiny, translating raw technical API calls into clear, business-context narratives. When compliance officers ask "what did the agent do?", you can generate audit-ready reports in minutes, not weeks. This feature ensures every agent action is recorded in language that stakeholders and auditors understand, making it indispensable for operating in heavily regulated industries.

Enterprise-Grade Security & Integration

Built with production-scale and security in mind, Prefactor delivers SOC 2–ready controls, emergency kill switches for agents, and native support for OAuth/OIDC. It seamlessly integrates with popular agent frameworks like LangChain, CrewAI, and AutoGen, as well as the emerging Model Context Protocol (MCP). This allows teams to deploy a robust governance layer in hours, not months, without rebuilding security infrastructure from scratch.

Use Cases of Prefactor

Scaling AI Agents in Regulated Finance

A Fortune 500 financial services company can use Prefactor to move AI agent pilots into full production. By providing clear audit trails that explain agent decisions in business terms and real-time monitoring of agent activity, Prefactor answers critical compliance questions, enabling secure deployment of agents for tasks like customer service analysis, fraud detection, and automated reporting within strict regulatory frameworks.

Ensuring Auditability in Healthcare Technology

Healthcare technology companies deploying AI agents for patient data analysis or operational automation face stringent HIPAA and other compliance requirements. Prefactor provides the immutable, context-rich audit trails and fine-grained access controls necessary to demonstrate exactly how patient data is accessed and used by autonomous agents, facilitating both internal governance and external audits.

Managing Multi-Agent Workflows in Enterprise SaaS

SaaS companies building complex, multi-agent workflows for their customers can use Prefactor as a central control plane. It allows them to govern dozens or hundreds of agent identities, monitor cross-agent interactions, control costs by tracking compute usage, and ensure that customer data is handled appropriately, all while maintaining a single pane of glass for operational management.

Securing Agent Access with Model Context Protocol (MCP)

As MCP becomes the standard for agents to access tools and data, production teams need to secure these connections. Prefactor provides the missing governance layer for MCP, enabling secure, authenticated, and auditable access between agents and servers. This use case is critical for teams adopting MCP who require enterprise-grade security and visibility beyond basic connectivity.

Frequently Asked Questions

What is an AI Agent Control Plane?

An AI Agent Control Plane is a centralized platform for governing the lifecycle of autonomous AI agents. Think of it like an identity and access management (IAM) system or a Kubernetes control plane, but specifically built for AI agents. It handles agent identity, authentication, authorization, real-time monitoring, audit logging, and policy enforcement, providing the operational and security oversight needed to run agents reliably in production environments.

How does Prefactor handle agent authentication and authorization?

Prefactor treats each AI agent as a first-class identity with its own credentials. It supports industry-standard protocols like OAuth 2.0 and OpenID Connect (OIDC) for secure authentication. Authorization is managed through fine-grained, policy-as-code rules that define what resources an agent can access and what actions it can perform. These policies can be version-controlled and automated within deployment pipelines, ensuring consistent and secure permissioning.

Can Prefactor integrate with our existing AI agent frameworks?

Yes, Prefactor is designed for interoperability. It offers seamless integration with leading AI agent frameworks and libraries such as LangChain, CrewAI, and AutoGen. It also provides robust support for the Model Context Protocol (MCP), which is becoming a default standard for agent-tool communication. This allows teams to add Prefactor's governance layer to their existing agent infrastructure without a costly rebuild.

Is Prefactor suitable for companies not in heavily regulated industries?

Absolutely. While Prefactor is engineered to meet the high demands of regulated sectors like finance and healthcare, its core benefits—clear visibility, operational control, cost tracking, and simplified auditability—are valuable for any company scaling AI agents. The platform prevents incidents, optimizes spending, and provides peace of mind, which accelerates safe and responsible AI deployment for businesses of all types.