RAG & Knowledge AIExample Solution

Internal Knowledge Platform for Operational Teams

B2B SaaS Company

A grounded internal knowledge assistant that answers operational questions from documentation, tickets, and policies — with citations and access control.

Problem

Operations and support teams spent hours daily searching documentation, prior tickets, and internal wikis to answer recurring questions. Information was fragmented across systems, inconsistent, and slow to find.

Solution

A RAG system that ingests documentation, tickets, and policies with incremental sync, applies document-level access control, and grounds every answer in cited sources with refusal behavior when evidence is missing.

Technology
  • OpenAI & Anthropic models
  • PostgreSQL + pgvector
  • Hybrid retrieval (vector + BM25)
  • Reranker
Automation
  • Incremental reindexing on document change
  • Query rewriting
  • Citation generation
  • Feedback loop into eval set
Outcome
  • Reduced average time-to-answer for internal queries
  • Every answer grounded in a citable source
  • Access control preserved at retrieval time
Architecture

A layered system

Each layer has a clear responsibility and a clear contract with the layers above and below. Read top-to-bottom for the request path; bottom-to-top for the data path.

  1. 01

    Ingestion

    Source connectors with change detection and incremental updates.

  2. 02

    Processing

    Chunking, embedding, and metadata extraction with source attribution.

  3. 03

    Retrieval

    Hybrid vector + keyword search with reranking and query rewriting.

  4. 04

    Generation

    Grounded answers with citations and refusal when evidence is missing.

  5. 05

    Safety

    Document-level access control and prompt-injection defenses.

Engagement

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