About AI Agents & RAG

An AI agent that hallucinates an answer is worse than no agent at all, which is why retrieval-augmented generation (RAG) matters: it grounds a model's answers in your actual documents, systems, and data instead of letting it guess. We build agents and RAG systems for specific, well-scoped tasks — internal knowledge search, customer support triage, structured data lookup — rather than open-ended “do anything” agents that are hard to trust in production. Every system we build includes a clear answer to the question of where the agent's information actually comes from.

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