Prefactor is an evaluation layer designed specifically for engineering teams shipping AI agents to end customers. While many AI agents pass standard offline evaluations, they often struggle or fail when deployed in real-world production environments. Prefactor bridges this critical gap by providing continuous, real-time observability and evaluation.

By scoring every agent run in real time, Prefactor helps developers surface quality regressions and model drift as soon as they happen. It gives engineering teams clear visibility into how their autonomous agents perform at scale, ensuring higher reliability and better user experiences in live environments.

Pros of Prefactor

Real-time scoring for every live AI agent run
Immediately surfaces quality regressions and performance drift
Bridges the gap between pre-deployment evals and real-world production performance
Provides engineering teams with detailed performance metrics at scale

Cons of Prefactor

Pricing details are not publicly provided in the metadata
Focuses specifically on real-time evaluation rather than agent building or hosting

Frequently Asked Questions

What is Prefactor?

Prefactor is an evaluation platform built for engineering teams that monitors and scores AI agent runs in real time within production environments.

What problem does Prefactor solve?

Many AI agents successfully pass pre-deployment evaluations but still fail in production. Prefactor closes this gap by tracking live agent behavior, identifying drift, and detecting quality regressions as they occur.