Agnost AI
Find recurring AI-agent failures in conversations and traces
Observe, evaluate, and control AI agent runs in production

Prefactor provides runtime monitoring, evaluation, and controls for AI agents. Developers instrument an application with its TypeScript or Python SDK to collect traces for model calls, tools, and decisions. Teams can then apply technical checks, model-based evaluations, qualitative scoring, and data-risk rules to understand how an agent behaves during real work.
Those evaluations can drive actions such as pausing a run for human approval, blocking an operation, or applying a limit through the SDK or API. Prefactor also supports custom spans with business context, versioned agents, separate deployment environments, and promotion based on evaluation results. It is intended for teams that need both execution records and configurable intervention in an agent workflow.
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