The Knowledge Base provides semantic search and retrieval capabilities for your document collections. Build RAG (Retrieval-Augmented Generation) applications by searching through vector-enabled documents and generating AI-powered answers from your data.

📖 Complete Knowledge Base Guide

Start here - Full documentation with examples, API reference, and usage patterns for the /knowledgebase-collection slash command

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Key Features

  • Semantic Search: Find relevant content using natural language queries across large document sets
  • AI-Powered Answers: Generate synthesized answers from your documents using RAG
  • Metadata Filtering: Target specific document subsets using attribute filters
  • Relevance Scoring: Get scored results based on semantic similarity
  • Flexible Output: Choose between raw search results or AI-generated summaries
  • Collection Management: Organize documents into separate vector stores for different use cases

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Common Use Cases

  • Documentation search and knowledge management systems
  • Customer support chatbots with company-specific knowledge
  • Internal Q&A systems for employee onboarding
  • Content discovery across large document repositories
  • Research assistance and information synthesis
  • Compliance and policy document search

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Using with Workflows

Select a knowledge base collection from the slash command menu to search and retrieve information. You can perform semantic searches, apply metadata filters, and generate AI-powered answers from your document collections. For complete usage details, examples, and API reference, see the Knowledge Base slash command documentation.