OpenRAG is a trust infrastructure for AI that verifies whether AI-generated answers are supported by their source context. It highlights risky or contradictory claims and refuses to endorse hallucinations. As AI systems move into research, enterprise, finance, and policy decisions, the cost of incorrect or overconfident answers becomes critical.
OpenRAG works as a model-agnostic verification layer that plugs into any LLM pipeline, API, or application. It breaks answers into claims, checks them against evidence, and generates human-readable trust reports with confidence and risk signals. OpenRAG aims to become the default verification standard for AI-generated content, similar to how SSL became essential for web security.
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