What is agent observability?

Capturing every agent run as structured trace data (each LLM call, tool invocation and decision) so you can see exactly what an agent did, how well it performed, and what it cost.

What is agent evaluation?

Continuously scoring agent outputs with the evals you define (LLM-as-judge, technical checks and qualitative metrics) on real production traffic, so you catch drift and regressions before your users do.

How do I instrument my agent with Prefactor?

Install the CLI (prefactor init) and add the TypeScript or Python SDK, native for LangChain, Claude, Vercel AI, OpenClaw and LiveKit. For coding and workflow tools, send OpenTelemetry spans, or instrument anything else with the core SDK. Minutes, no platform migration.

What are custom spans, and how do they measure quality?

A custom span marks a step that matters: a retrieval, a tool call, a sub-agent. You layer them in to run your own evals on it (LLM-as-judge, technical and qualitative metrics) and watch scores trend over time, with P95/P99 latency alongside, not just the final answer.

How does human-in-the-loop work?

High-risk actions can be paused and routed to a person to approve, modify or reject before they execute, via the SDK or the API, which enforces the decision at runtime. Every decision is logged.

How does Prefactor enforce at runtime?

Through the SDK or API, Prefactor can pause a run and hold a high-risk action for human approval before it executes. Sensitive-data detection and risk classification drive what gets held.

Why do AI agents need identity and scoped access?

So each action ties to a specific agent, task and user context, enabling least privilege, traceability and revocation.

Prefactor

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Agent observability and evaluation platform for production AI agents, scoring every run in real time.

FreemiumAI Agent AI Analytics

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What is Prefactor?

Prefactor is an agent observability and evaluation platform that scores every run in production for quality, drift, and risk, then wires those evaluations into action. It provides real-time tracing, custom evals, and runtime enforcement with human-in-the-loop approval. The platform integrates with TypeScript and Python SDKs, native for LangChain, Claude, Vercel AI, OpenClaw, and LiveKit, and supports custom spans to bring any datasource into the run. Prefactor also offers versioning, staging, and promotion for agents, plus enterprise security features.

What can Prefactor do?

Real-time evaluation
Scores every run in production for quality, drift, and risk.
Runtime enforcement
Holds, approves, or blocks risky actions via SDK or API.
Custom spans
Attach any datasource to a run for grounded evals.
Versioning & promotion
Version agents, promote through dev/staging/prod with eval gates.
Native SDK integrations
TypeScript & Python SDKs for LangChain, Claude, Vercel AI, OpenClaw, LiveKit.
Sensitive-data detection
Detects 17 categories of sensitive data in agent traffic.
Human-in-the-loop
Pause high-risk actions for human approval before execution.

Who is Prefactor for?

AI engineering teams: Score every production agent run for quality, drift and risk as it happens so a failing agent is caught live instead of in a later report.
Reliability teams: Pause risky runs and enforce policies at runtime through the SDK or API to keep production agents within guardrails.
Compliance & risk teams: Detect sensitive data across agent traffic and route high-risk actions to a person for approval before they execute.
Platform teams: Version agents and promote them through dev, staging and production behind eval-gated checks to track quality release over release.