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Agentic RAG

Build an AI-powered knowledge base that understands your docs

Transform your static documentation into an intelligent knowledge base. Users ask questions in natural language and get synthesized answers drawn from across your entire doc library — with citations, follow-up suggestions, and automatic gap detection.

Stack

EigenForge Agent ForgeVector databaseDocument ingestion pipelineLLM for synthesis

Implementation

  1. 1

    Build the ingestion pipeline

    Connect to your doc sources — Notion, Confluence, Google Docs, markdown repos. Set up automatic re-indexing when documents change.

  2. 2

    Create the search agent

    Build an agent that performs multi-query retrieval — decomposing complex questions into sub-queries, searching across collections, and merging results.

  3. 3

    Add synthesis and citation

    Configure the agent to synthesize information from multiple sources into a coherent answer, with inline citations linking back to source documents.

  4. 4

    Implement gap detection

    When the agent can't find an answer, it logs the gap. Over time, this builds a map of missing documentation that your team can fill.

  5. 5

    Deploy the knowledge base

    Ship as a searchable interface, API, or Slack bot. Monitor query patterns to continuously improve content coverage.

What You Get

  • Natural language search across all your documentation
  • Synthesized answers with citations from multiple sources
  • Automatic detection of documentation gaps
  • Self-improving knowledge base that gets better with usage

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