RagMetrics is the GenAI evaluation platform that helps AI professionals, AI SaaS business owners, and product teams build reliable, trustworthy AI systems. Our platform systematically evaluates and scores every generative AI output against 200+ content and context criteria, including hallucination risk, factual accuracy, retrieval grounding, structure, and domain alignment.

Unlike tools that only monitor performance or provide infrastructure-level metrics, RagMetrics is the application-level evaluation layer for GenAI. We turn subjective testing into continuous, data-driven quality assurance by scoring, explaining, and tracing every model output.

With flexible deployment options—SaaS, private cloud, or on‑premises—RagMetrics fits into your existing workflow. We work with all major LLM providers including ChatGPT, Google Gemini, Claude, while supporting custom models, with quality and accuracy testing that ensures your AI behaves as expected before it reaches users.

RagMetrics delivers:
 • Actionable output scoring across hallucination detection, relevance, completeness, and policy fit
 • Transparent explanations that clarify why a score was assigned
 • Real‑time and batch evaluation for experiments, apps, and review workflows
 • Enterprise‑grade audit trails for regulated or mission‑critical applications

Built for today’s AI builders, RagMetrics turns GenAI quality from guesswork into measurable standards.

📍 Miami HQ | Serving developers and enterprise teams worldwide

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