Daiquest wins RAG-based medical science knowledge service contract
The company will apply its Q-RAG solution to the National Medical Science Knowledge Center's search service, pairing AI answers with cited sources.
Daiquest said on October 28, 2026, that it has been selected as the contractor for the National Institute of Health's project to build an intelligent service based on RAG over national medical science knowledge resources.
The core of the project is to apply Daiquest's RAG solution, Q-RAG, to the keyword-centred search service on the National Medical Science Knowledge Center's website, creating an AI knowledge service that answers with supporting evidence.
The new service uses hybrid search that combines keyword search with semantic search. On the answer screen, AI-generated content and the source documents appear side by side, with provenance information such as document name and page number.
It draws on a Korean embedding model specialised for the medical science field and the company's own local LLM. The system is built with a hybrid structure that combines Q-RAG's vector database with the indexing and dictionary resources of the search engine currently operated by the National Medical Science Knowledge Center.
The contract was reported by datanet.co.kr.
Quick answers
What is Daiquest's role in the project?
Daiquest has been selected as the contractor for the National Institute of Health's RAG-based intelligent service project and will supply its Q-RAG solution.
How will the new service answer questions?
It uses hybrid search combining keyword and semantic search, and displays AI-generated answers alongside source documents with provenance such as document name and page number.