Prefactor

About Prefactor

Prefactor is the enterprise-grade control plane for AI agents, designed to solve the critical governance gap that prevents AI agent pilots from moving into secure, compliant production. It provides a centralized platform for managing AI agent identity, access, and auditability at scale. Built specifically for product and engineering teams within regulated enterprises—such as financial services, healthcare, and mining—Prefactor transforms complex agent authentication and authorization into a single, elegant layer of trust. The platform delivers SOC 2–ready security, enabling companies to align security, product, engineering, and compliance teams around one source of truth. By providing real-time visibility, human-delegated control, and business-context audit trails, Prefactor eliminates the need to rebuild governance from scratch, reducing time-to-production for agent deployments from months to hours and ensuring every agent action is authenticated, scoped, and auditable.

Features of Prefactor

Real-Time Agent Monitoring & Dashboard

Gain complete operational visibility across your entire agent infrastructure from a single dashboard. Track every AI agent in real-time to see which are active, what tools and data they are accessing, and where failures or anomalies emerge—allowing you to proactively address issues before they cascade into costly incidents. This feature provides the shared visibility that engineering, security, and product teams need to manage agents confidently at scale.

Compliance-Ready Audit Trails

Move beyond cryptic API logs to audit trails that speak business language. Prefactor translates every agent action into clear, stakeholder-friendly context, detailing what was done and why. This enables teams to generate audit-ready reports for compliance reviews in minutes, not weeks, and provides definitive answers to regulatory inquiries, ensuring audit trails can withstand rigorous scrutiny in regulated industries.

Identity-First Access Control

Apply proven human identity governance principles to your AI agents. Prefactor assigns every agent a first-class, auditable identity with dynamic client registration. Access is managed through fine-grained role and attribute controls and policy-as-code, allowing permissions to be automated within CI/CD pipelines. This ensures every action is authenticated and every permission is precisely scoped, creating a foundational layer of trust.

Enterprise Security & Integration

Built for regulated environments, Prefactor delivers enterprise-grade security with SOC 2 readiness, emergency kill switches for agent control, and interoperable OAuth/OIDC support. It seamlessly integrates with popular agent frameworks like LangChain, CrewAI, and AutoGen, as well as custom builds, allowing for deployment in hours rather than months. This turnkey infrastructure ensures scalability and compliance from day one.

Use Cases of Prefactor

Accelerating Agent Deployment in Regulated Enterprises

For financial services or healthcare companies stalled in pilot purgatory, Prefactor provides the governance framework to secure executive and compliance approval. By delivering the necessary audit trails, access controls, and real-time monitoring, it enables teams to move AI agent projects from proof-of-concept to fully sanctioned, secure production deployments, dramatically accelerating time-to-value.

Centralizing Governance for Multiple Agent Pilots

Organizations running concurrent AI agent experiments across different departments can use Prefactor as a single control plane. It consolidates management, providing unified visibility, policy enforcement, and cost tracking across all agents. This prevents shadow IT, reduces risk, and allows platform teams to govern faster with a consistent source of truth for all agent activity.

Simplifying Compliance and Audit Reporting

When facing internal or external audits, teams can use Prefactor to instantly generate clear, comprehensible reports of all agent activity. Instead of spending weeks manually correlating API logs, compliance officers get pre-translated audit trails that explain agent actions in business terms, significantly reducing the overhead and cost associated with compliance verification.

Optimizing Agent Performance and Cost

Beyond security, Prefactor’s monitoring and cost-tracking capabilities allow engineering leaders to identify inefficient agent patterns and optimize compute spending across providers. By gaining visibility into which agents are most active and resource-intensive, teams can right-size deployments, improve performance, and directly impact the bottom line by controlling cloud infrastructure costs.

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 autonomous AI agents. Prefactor’s control plane specifically handles agent identity, authentication, authorization, real-time monitoring, and audit logging. It is the essential infrastructure that allows enterprises to deploy agents at scale with the same level of control and visibility they have over human users and traditional software.

How does Prefactor handle authentication for AI agents?

Prefactor moves beyond basic M2M (Machine-to-Machine) tokens by giving each AI agent a first-class, unique identity with dynamic client registration. It supports industry-standard OAuth 2.0 and OpenID Connect (OIDC) protocols for interoperable, secure authentication. Access is then governed through fine-grained, policy-as-code controls that define what each identified agent is permitted to do, ensuring delegated and auditable access.

Is Prefactor built for specific AI agent frameworks?

Yes, Prefactor is designed to be framework-agnostic and integrates seamlessly with popular agent development frameworks including LangChain, CrewAI, and AutoGen, as well as custom-built agent architectures. This allows teams to adopt Prefactor without rebuilding their existing agent code, enabling deployment and governance in hours rather than months.

Why is agent governance critical for moving from POC to production?

In a proof-of-concept, the focus is on functionality. In production, especially within regulated enterprises, the requirements expand to include security, compliance, auditability, and cost control. Without a governance layer like Prefactor, teams cannot answer critical questions from security and compliance teams about what agents are doing, leading to deployment blockers. Prefactor provides the necessary controls to meet production-grade standards and gain organizational approval.