Prefactor

Prefactor is the essential control plane for AI agents, built to help engineering and product teams scale securely from experimental pilots to governed production deployments. It solves the critical infrastructure gap that emerges when AI agents move beyond demos: the lack of visibility, control, and auditability. In regulated industries like finance, healthcare, and mining, where "move fast and break things" is not an option, Prefactor provides the enterprise-grade governance layer that security, engineering, and compliance teams can align around. Its core value proposition is turning the complex challenge of agent authentication and authorization into a single, elegant layer of trust. By giving every AI agent a first-class, auditable identity with dynamic registration and fine-grained access controls, Prefactor enables companies to maintain full visibility over every agent action, automate permissions via policy-as-code, and generate business-context audit trails that satisfy strict regulatory scrutiny. Built for scalability and compliance from the ground up with SOC 2-ready security, Prefactor allows teams to stop rebuilding foundational security infrastructure and focus on building innovative agents.

Real-Time Agent Monitoring

Gain complete operational visibility across your entire agent infrastructure. Track every agent in real-time through a centralized dashboard to see which agents are active, what resources they're accessing, and where issues or failures emerge before they cascade into incidents. This allows platform and engineering teams to maintain control and ensure system health.

Identity-First Control & Governance

Prefactor brings proven governance principles to AI agents by providing each one with a first-class, auditable identity. Every agent action is authenticated and every permission is dynamically scoped with fine-grained access controls. This identity layer enables secure, policy-as-code automation within CI/CD pipelines for scalable management.

Compliance-Ready Audit Trails

Move beyond cryptic API logs. Prefactor's audit system translates technical agent actions into clear business context, creating audit trails that stakeholders and compliance officers can understand. Generate audit-ready reports in minutes to demonstrate exactly what your agents did and why, satisfying rigorous regulatory scrutiny.

Emergency Kill Switches & Cost Tracking

Maintain ultimate control with human-delegated emergency kill switches to instantly halt agent operations if needed. Coupled with detailed cost tracking across compute providers, Prefactor helps you identify expensive patterns, optimize spending, and maintain both financial and operational governance over your agent deployments.

Scaling AI Pilots to Regulated Production

For enterprises in finance or healthcare running multiple AI agent proofs-of-concept, Prefactor provides the missing governance layer to gain security and compliance approval for production deployment. It aligns teams around a single source of truth, enabling a secure transition from demo to live environment without rebuilding security.

Centralized Governance for Multi-Agent Ecosystems

Organizations using various agent frameworks like LangChain, CrewAI, or AutoGen can use Prefactor as a unified control plane. It offers a single dashboard to monitor, manage, and audit all agents regardless of their underlying technology, simplifying oversight and enforcing consistent security policies across complex ecosystems.

Automating Compliance for Autonomous Operations

In industries with strict regulatory requirements, Prefactor automates the creation of detailed, business-context audit logs. This use case is critical for answering compliance inquiries about agent activity, generating mandatory reports efficiently, and providing an immutable record that withstands audits from financial or healthcare regulators.

Optimizing Agent Performance and Cost

Engineering and product teams leverage Prefactor's real-time monitoring and cost-tracking features to identify performance bottlenecks, debug failures, and analyze spending patterns. This visibility allows for proactive optimization of agent workflows and infrastructure costs, ensuring efficient and reliable scaling.

What is an AI agent control plane?

An AI agent control plane is a centralized governance layer that provides visibility, security, and operational control over autonomous AI agents. Think of it like IAM (Identity and Access Management) or a dashboard for human users, but built specifically for AI agents. It manages agent identities, permissions, auditing, and monitoring to enable secure, scalable deployments.

How does Prefactor integrate with existing AI agent frameworks?

Prefactor is designed for interoperability and works seamlessly with popular frameworks like LangChain, CrewAI, AutoGen, and custom-built agents. Integration typically involves using Prefactor's SDKs to register agents and define policies, allowing teams to deploy the control plane in hours, not months, without overhauling their existing agent code.

Is Prefactor suitable for non-regulated industries?

Absolutely. While built with the stringent requirements of regulated industries in mind, any engineering team scaling multiple AI agents benefits from centralized visibility, cost control, and operational oversight. Prefactor solves universal challenges of managing production AI agents, preventing incidents and simplifying governance for all growing companies.

What does "SOC 2-ready" security mean?

Prefactor is engineered from the ground up with enterprise security standards, including the controls necessary for a SOC 2 Type II compliance audit. This means the infrastructure has built-in security measures for data protection, access management, and auditability, giving security and compliance teams confidence in the platform's robustness for sensitive environments.