Multi-Turn Retrieval

What is multi-turn retrieval?

A conversation isn't one question and one answer — topics keep deepening as you go. Multi-turn retrieval lets the system search again and again across the turns, pulling in fresh context as the dialogue moves forward, instead of searching once and calling it done.

Why isn't a single search enough?

Questions build on each other
First "what is RAG?", then "how does it differ from fine-tuning?" — the material the second question needs wasn't fetched the first time.
New info spawns new questions
After the AI answers, a follow-up often builds on that very answer and needs extra material.

How does it work?

Carry the conversation history
Each turn's search includes the previous turns, so the system knows what the user is really asking now.
Top up dynamically
When information runs thin, search again and add the new snippets to the context for a fuller answer.
Pace the searching
It doesn't search every single line — the system judges when to look things up and when to answer directly.

What problem does it solve?

Multi-turn retrieval stops an AI from going forgetful or blank mid-conversation. It follows the thread, tops up the material, and keeps every answer standing on the latest, fullest information — the key skill of a chat-based RAG system.

Bottom line: multi-turn retrieval is searching as you chat — wherever the conversation goes, the material follows.