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Tech · RAG_KNOWLEDGE_CORE

Knowledge RAG Agent

Grounded answers from your internal documentation and data

Retrieval-augmented generation over wikis, SOPs, product docs, and ticket history — with citation links, access controls, and freshness monitoring.

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Business problem

Employees waste hours searching fragmented knowledge bases and receive inconsistent answers from generic chatbots that hallucinate outside your corpus.

Intended users

  • Internal enablement and L&D teams
  • Support leads building deflection content
  • Engineering managers documenting runbooks

Key outcomes

  • Sub-second semantic search across approved document sets
  • Every answer includes source citations and confidence scoring
  • Role-based corpus visibility aligned to your IdP groups
  • Stale-content alerts when indexed documents exceed TTL thresholds

Visual workflow

workflow / agent-pipelineIllustrative
  1. 01

    Input

    User query arrives via chat widget, Slack bot, or API with session identity and permitted corpus scopes.

  2. 02

    Agent

    Hybrid retrieval (vector + keyword) fetches top chunks; the LLM synthesises a grounded response with inline references.

  3. 03

    Validation

    Citation integrity checks, toxicity filters, and out-of-corpus detection flag low-confidence or policy-violating drafts.

  4. 04

    Human Review

    Ambiguous or sub-threshold answers route to a subject-matter expert queue with the retrieved context attached.

  5. 05

    Action

    Approved responses are delivered to the user channel; negative feedback triggers re-index or content-gap tickets.

  6. 06

    Record

    Query, retrieved chunk IDs, model version, latency, and feedback rating are logged for analytics and tuning.

Inputs

  • • Confluence, Notion, SharePoint, or S3 document exports
  • • Structured FAQ and product metadata tables
  • • Group-to-corpus access mappings from your IdP
  • • Synonym and acronym glossaries for domain terms

Outputs

  • • Grounded chat responses with clickable citations
  • • Content-gap reports by topic cluster
  • • Relevance tuning dashboards
  • • Exportable conversation transcripts (redacted)

Integration categories

Knowledge bases & wikisIdentity providersChat & collaboration toolsVector databases

Human review points

  • • Answers below confidence threshold on regulated topics
  • • New corpus ingestion before production promotion
  • • User-reported incorrect citations

Security & data handling

  • • Embeddings and chunks isolated per tenant
  • • Document ACLs enforced at retrieval time, not post-generation
  • • Optional on-prem or VPC deployment for sensitive IP

Deployment process

  1. Inventory knowledge sources and define access tiers
  2. Ingest pilot corpus and benchmark retrieval quality
  3. Connect chat surfaces and enable feedback loops
  4. Expand sources, schedule re-index jobs, and train power users

FAQ

How often is content re-indexed?

Connectors support webhook-driven incremental updates plus scheduled full re-index windows you configure per source.

Can we restrict answers to a single department's docs?

Yes. Corpus scopes bind to IdP groups so finance, legal, and engineering each see only authorised material.

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