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Plurai lets developers define what their AI agents should and shouldn't do in plain language, then automatically generates training data, validates it, and deploys a fine-tuned evaluation model within minutes
Plurai lets developers define what their AI agents should and shouldn't do in plain language, then automatically generates training data, validates it, and deploys a fine-tuned evaluation model within minutes. Built for teams needing reliable AI agent monitoring, it uses small language models to deliver sub-100ms latency at a fraction of the cost of LLM-as-judge approaches. It eliminates the need for annotation pipelines or prompt engineering, providing always-on guardrails rather than sampled checks.
Plurai generates training data, validates it, and deploys a fine-tuned evaluation model within minutes.
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