Retrieval-Augmented Generation (RAG) connects Large Language Models with your own documents, databases, knowledge bases, and business information.
Instead of relying only on a model’s existing knowledge, RAG applications retrieve relevant information when needed and use that context to provide more useful responses.
Help employees find answers quickly across internal documents and business knowledge.
Search large volumes of business information using natural-language queries.
Ask questions about reports, manuals, policies, contracts, and other business documents.
Give support teams and customers access to relevant product and service information.
Build tailored RAG solutions around your specific data, workflows, and business requirements.