Prefactor

About Prefactor

Prefactor is the essential control plane for AI agents, designed to bridge the critical gap between experimental proof-of-concept and secure, compliant, and scalable production deployment. In an era where autonomous AI agents are rapidly evolving from demos to core operational components, organizations face immense challenges in governance, visibility, and security. Prefactor directly addresses this by providing every AI agent with a first-class, auditable identity, transforming how enterprises manage their automated workforce. It is built specifically for product, engineering, security, and compliance teams within regulated enterprises—such as those in financial services, healthcare, and mining—who are running multiple agent pilots and need a unified source of truth. The platform's core value proposition lies in turning the complex, fragmented challenge of agent authentication and authorization into a single, elegant layer of trust. By offering dynamic client registration, fine-grained role-based access control, policy-as-code management, and full auditability, Prefactor enables companies to govern their AI agents at scale with confidence, ensuring that innovation can proceed without compromising on security or regulatory requirements.

Features of Prefactor

Identity-First Agent Governance

Prefactor assigns a unique, first-class identity to every AI agent in your ecosystem, applying proven human identity governance principles to the world of autonomous software. This foundational feature ensures every action an agent takes is authenticated and every permission is explicitly scoped. Through dynamic client registration and delegated access controls, you can manage agent identities as seamlessly as user identities, providing a robust framework for secure interactions with tools and data via protocols like MCP (Model Context Protocol).

Real-Time Visibility & Monitoring

Gain complete operational oversight with a centralized dashboard that monitors all agent activity in real time. This feature allows teams to see which agents are active, what resources they are accessing, and where errors or performance issues are emerging—all before they escalate into full-blown incidents. It moves teams from a state of flying blind to having immediate, actionable insights into their entire agent infrastructure, enabling proactive management and swift troubleshooting.

Compliance-Ready Audit Trails

Prefactor’s audit logs are engineered for regulatory scrutiny, translating raw technical API events into clear, business-context narratives. When compliance officers or auditors ask "what did this agent do?", you can provide straightforward answers instead of cryptic log files. This feature automates the generation of audit-ready reports in minutes, capturing the who, what, when, and why of every agent action in language that stakeholders across the organization can understand.

Policy-as-Code & Automated Permissions

Securely manage and scale agent access through codified policies that integrate directly into your CI/CD pipeline. This feature enables engineering and security teams to define, version-control, and automate permission grants and revocations. By treating security policies as code, Prefactor ensures consistent enforcement, reduces human error, and allows permissions to evolve automatically alongside your agent deployments, maintaining both security agility and rigor.

Use Cases of Prefactor

Scaling AI Pilots to Regulated Production

For enterprises running successful AI agent proofs-of-concept, the journey to production is often blocked by security and compliance hurdles. Prefactor provides the governance layer needed to gain internal approval, offering the audit trails, access controls, and visibility that risk and compliance teams demand. This enables organizations to confidently transition from limited demos to full-scale, operational deployments within regulated environments like finance or healthcare.

Centralized Governance for Multi-Framework Agent Fleets

Companies utilizing a mix of AI agent frameworks (e.g., LangChain, CrewAI, AutoGen) or custom-built agents struggle with inconsistent management and security postures. Prefactor acts as a universal control plane, bringing all agents under a single pane of glass. This unified approach standardizes identity, enforces consistent policies, and provides aggregated monitoring and reporting, regardless of the underlying technology stack.

Proactive Incident Prevention and Cost Optimization

With real-time monitoring and detailed cost tracking across cloud providers, Prefactor empowers platform teams to identify inefficient agent patterns, unexpected behaviors, or spiraling compute costs before they impact the business. This use case focuses on operational excellence, allowing teams to optimize resource allocation, terminate malfunctioning agents, and ensure reliable, cost-effective agent performance.

Streamlining Compliance and Audit Reporting

In industries with stringent regulatory requirements, manually preparing audit reports for AI agent activity is a slow and error-prone process. Prefactor automates this burden by generating comprehensive, stakeholder-friendly reports that detail agent actions with business context. This significantly reduces the time and resources spent on compliance activities, from weeks to minutes, and ensures readiness for internal or external audits.

Frequently Asked Questions

What is an AI Agent Control Plane?

An AI Agent Control Plane is a centralized management layer that provides governance, security, and operational oversight for fleets of autonomous AI agents. Think of it like an identity and access management (IAM) system or a Kubernetes control plane, but specifically designed for AI agents. It handles critical functions such as assigning identities, enforcing access policies, monitoring activity in real-time, maintaining audit trails, and enabling emergency interventions, ensuring agents operate securely and compliantly at scale.

How does Prefactor handle authentication for agents?

Prefactor provides robust, identity-first authentication for AI agents, moving beyond simple API keys or insecure M2M (machine-to-machine) tokens. It supports industry-standard protocols like OAuth 2.0 and OpenID Connect (OIDC), allowing for secure, delegated access. Each agent gets a unique identity credential, and its access to tools and data is governed by fine-grained, auditable policies. This approach is particularly compatible with emerging standards like the Model Context Protocol (MCP) for secure tool integration.

Is Prefactor only for large, regulated enterprises?

While Prefactor is engineered to meet the high-security and compliance demands of regulated industries like banking and healthcare, its core benefits are valuable for any organization scaling AI agents beyond a simple demo. Startups and tech companies that prioritize security, need operational visibility, want to avoid rebuilding governance from scratch, or are preparing for future compliance requirements will find Prefactor essential for sustainable and secure agent deployment.

Can Prefactor work with our existing AI agent frameworks?

Yes, Prefactor is designed for interoperability. It provides integrations and supports standard protocols that work with popular AI agent frameworks and libraries such as LangChain, CrewAI, and AutoGen, as well as custom-built agent systems. The platform acts as an independent control layer, meaning you can integrate it with your existing agent infrastructure to add governance without needing to rebuild your agents from the ground up.