Prefactor
Prefactor is a real-time agent evaluation platform that closes the gap between observing an AI agent's behavior and intervening when something goes wrong.
Our verdict
Who it's for
Real-time agent evaluation and automated guardrails for production AI
Who should look elsewhere
Requires SDK instrumentation, which may add overhead for simple or low-volume agent deployments.
Pros
- +Enforces guardrails at runtime, not just after analysis, catches failures live.
- +Supports complex multi-agent and multi-layer architectures with per-layer risk tracking.
- +Integrates deeply with popular agent frameworks and voice stacks without requiring pipeline changes.
Cons
- −Requires SDK instrumentation, which may add overhead for simple or low-volume agent deployments.
- −Human-in-the-loop features may introduce latency for time-sensitive agent actions.
Key features
- ✓Real-time agent evaluation with LLM-as-judge, technical, and qualitative metrics on every run.
- ✓Runtime enforcement: block, throttle, or require human approval for risky actions via SDK or API.
- ✓Custom spans to attach context from any datasource (GitHub, Linear, Jira, databases, internal APIs) to agent runs.
- ✓Human-in-the-loop handoff built into span structure for support agents and voice agents.
- ✓PII detection and automatic redaction of sensitive data in agent conversations.
- ✓Per-layer risk profiling for multi-tier agents (e.g., conversational vs. background agent).
- ✓p95/p99 tracking per span type for latency, cost, and quality together.
- ✓Proactive alerts on real patterns like spikes in negative feedback, not single events.
Pricing
| Plan | Price | Billing | Notes |
|---|---|---|---|
| Free | — | month | 1,000,000 free spans for the first 50 sign ups; US$2,500 of usage, on us |
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