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Hybrid RAG

Hybrid RAG (Retrieval-Augmented Generation) mixes lexical search (exact tokens, SKUs, error codes, policy IDs) with vector / semantic search (paraphrases and conceptual similarity). The merged results ground the model so answers stay tied to your documents instead of free-form guessing.

Short definition (citation-ready)​

Hybrid RAG retrieves supporting passages using both keyword-oriented and embedding-oriented search, fuses ranked results, and passes them to a language model to generate an answer — ideally with citations back to sources.

Why hybrid beats “vectors only”​

Query typeVectors aloneLexical aloneHybrid
“What is your refund policy?”StrongMediumStrong
“Error E-4421 meaning”Weak/mediumStrongStrong
“SKU A12-900 warranty”WeakStrongStrong
“How do I change billing email?”StrongMediumStrong

Enterprise corpora are full of identifiers. Pure semantic search misses them; pure keyword search misses paraphrase. Hybrid covers both.

Architecture​

Hybrid RAG inside an AI Knowledge Platform​

Hybrid RAG is the retrieval engine. An AI Knowledge Platform wraps it with ingest, workspace isolation, OCR, and ops. In Qefro:

  • Indexes are per workspace inside a tenant
  • Customer AI and Employee AI both consume hybrid retrieval
  • Citations help operators verify groundedness

Platform detail: Knowledge Platform.

Quality loop​

Improve Hybrid RAG quality

  1. Curate sources — Remove duplicates and contradictory drafts.
  2. Test identifier queries — SKUs, error codes, policy numbers.
  3. Test paraphrase queries — Natural language variants of the same intent.
  4. Inspect citations — Wrong citation ⇒ fix chunking or source, not only the prompt.
  5. Refuse when empty — Prefer honest gaps over hallucinated policy.

Best practices​

  • Keep chunk sizes appropriate for your docs (too large → noisy; too small → broken identifiers).
  • Re-index after major policy edits; do not rely on chat memory.
  • Separate customer-safe and internal corpora (Customer AI vs Employee AI).
  • Pair RAG with Business Actions only when live data is required — docs for policy, APIs for state.

FAQ​

Is Hybrid RAG the same as an agent?
No. RAG retrieves knowledge for answering. Agents/tools (Business Actions) call APIs. Production systems often use both.
Does Hybrid RAG prevent hallucinations?
It reduces unsupported answers when retrieval and prompting are solid, but it does not eliminate model error. Citations and refusals are essential.
Do I need Hybrid RAG for Employee AI?
Yes if employees ask against internal docs. The same retrieval stack powers Internal Portal workspaces.