engineering · 1 min read
Parent-Document Retrieval: Small Chunks, Big Context
Retrieve on small chunks for precision, return parent documents for context. The technique Bhogar AI uses to make RAG answers feel complete.
BABhogar AI TeamProduct & Engineering
Small chunks retrieve precisely. Large chunks give the LLM enough context to answer well. You can have both: retrieve on small chunks, then fetch the parent document for the LLM.
Why it matters
Pure small-chunk retrieval often returns the right idea but missing the supporting context. Pure large-chunk retrieval drowns the right idea in noise. Parent-document retrieval is the proven middle path.
How Bhogar AI approaches it
Bhogar AI ships parent-document retrieval as a one-toggle option on every KB. We index small chunks for retrieval, store a pointer to the parent, and assemble the parent (or a contextual window around the chunk) at generation time.
- One-toggle parent-document retrieval per KB
- Configurable parent size: paragraph, section or full document
- Compatible with hybrid and graph retrieval
- Citations point to the original chunk inside the parent
- Per-KB latency budget with graceful fallback
What you get
On long-form QA tasks parent-document retrieval lifts answer faithfulness 10-20 points over plain small-chunk RAG.