Plurai
Vibe-train evals and guardrails tailored to your use case
In plain words
Plurai is a developer tool that creates custom evaluation models and guardrails for AI agents without requiring labeled data or manual annotation. Users describe desired and undesired agent behaviors, and Plurai automatically generates training data, validates it, and deploys a specialized model within minutes. The system uses small language models to achieve sub-100ms latency while reducing costs compared to GPT-based evaluation and significantly lowering failure rates in production deployments.
written from the facts on this page · September 2026
From the sources
Vibe training for AI agent reliability. Describe what your agent should and should not do — Plurai generates training data, validates it, and deploys a custom model in minutes. It feels like vibe coding, but for evaluation and guardrails. No labeled data. No annotation pipeline. No prompt engineering. Under the hood, small language models deliver sub 100ms latency, 8x lower cost than GPT as judge, and over 43% fewer failures. Always on, not sampled. Built on published research (BARRED).
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