You build with one and evaluate with the other, so they are not alternatives: Prefactor watches production runs on any framework, weighing outcome quality and cost.
An agent platform builds and runs agents on its own framework; Prefactor evaluates the runs those agents produce in production, whatever framework built them. Ship the agent with a platform, then add Prefactor when you need a quality score, drift detection, and cost per agent.
| Decision factor | Agent platforms | Prefactor |
|---|---|---|
| Where it fits | Building and running the agent | Telling you how the agent is doing |
| Lifecycle stage | Development and deployment | Production time |
| Framework scope | Builds and runs agents on its own framework | Scores agents from any framework |
| What it measures | Logs, latency, and cost for its own runtime | A quality score, drift, and cost per agent |
| How it attaches | You build the agent on it | Native SDK, core SDK, or OpenTelemetry ingest, no rebuild |
| Use them together? | Build with an agent platform | Evaluate with Prefactor |
Best for engineering teams building agents and moving quickly from idea to a running system.
Best for teams running agents in production who need to know each one is doing its job across whichever platforms built them.
| Capability | Agent platforms | Prefactor |
|---|---|---|
| Building and running agents | ||
| Orchestration (tools, memory, reasoning) | ✓ | — |
| Deployment infrastructure | ✓ | — |
| Native logs, latency, and cost | ✓ | For its own runtime |
| Evaluating the outcome | ||
| Quality score per run | — | ✓ |
| Quality score tracked per agent and version | — | ✓ |
| Drift detection after a model or prompt change | — | ✓ |
| Cost attributed per agent and version | Per platform, build it yourself | ✓ |
| Across your stack | ||
| Scores agents built on other frameworks | — | ✓ |
| Works with custom agents | Partial | ✓ |
| One queryable record per agent | — | ✓ |
| Audit trail for a decision | — | ✓ |
We sell the layer this section describes. Read it with that in mind.
An agent platform answers how you build and run an agent; its monitoring reports what a run did inside its own runtime. Neither says whether the agent did its job, at acceptable quality and cost.
The platform that runs an agent is also the one grading its own homework. Prefactor sits outside the runtime and puts a verdict on each run.
A platform only sees the agents built on it. Prefactor keeps one record across every framework in your stack.
The quality score is tracked per agent across versions, and a behaviour shift after a change is flagged rather than buried in logs.
It reads the traces your agents already emit, through a native SDK or any OpenTelemetry source, so you keep what you built.
Book a demo and we will evaluate a live agent on a fleet like yours: quality per run, drift after a change, and cost per agent, across whichever frameworks built them.
Prefactor helps teams observe, evaluate, and improve their AI agents in production, across every framework and provider.