---
title: Introduction
description: What Prefactor is, how the platform is structured, and where to
  find what you need.
editUrl: true
head: []
template: doc
sidebar:
  hidden: false
  attrs: {}
pagefind: true
draft: false
---

Prefactor is an AI oversight and performance management platform focused on quality, risk, and auditability. You instrument your agents with the SDK; we record every run as a structured sequence of spans, score the data they touch against a risk profile, and track every version that has ever run. The web platform is where you inspect that record, apply governance controls, and produce the evidence a compliance review needs.

## From pilot to production

Prefactor is designed to grow with your agents.

**Pilot.** Instrument your first agent with the SDK. You immediately get span-level activity records — LLM calls, tool invocations, and agent spans — visible in the Instances view. The default schema covers you at this stage; no custom schema or risk profile is required.

**Adding structure.** Move from permissive default schemas toward tighter [activity schema](/platform/concepts/activity-schema) definitions where you need clearer contracts. Once those definitions deploy, the web app shows conformance status for each span type and flags gaps. Assign a [risk profile](/platform/concepts/risk-profile) to the agent to start classifying the data it handles.

**Going to production.** When you deploy your agent to production, create a Production [environment](/platform/concepts/environment) in Prefactor to go alongside your existing Development one. Activity from each deployment is tracked separately, so you can see exactly what is running where.

**Evidence and audit.** Every instance, span, schema version, and risk classification is accessible in Prefactor — giving you a complete record of what your agents did and what data they touched.