RAG (Retrieval-Augmented Generation)

RAG tools provide the pipeline to connect an AI model to your private data (documents, databases, wikis). Instead of relying only on what the AI was trained on, RAG tools "retrieve" relevant facts from your company's data and "augment" the AI's answer, ensuring accuracy and context. Examples Vector Databases: Specialized storage that allows AI to search data by "meaning" rather than just keywords. Document Parsers: Tools that chop up messy PDFs and spreadsheets into clean chunks of text for the AI to read. Hybrid Search: Search engines that combine keyword matching with AI semantic search for better results. Knowledge Graph Creation: Mapping connections between data points (e.g., "CEO" is linked to "Company") to help the AI understand relationships.

10 tools