Digital librarian AI agent that connects SQL data with vector-searchable documents
An AI agent that separates the factual part of a question from the contextual part, retrieves precise values from SQL databases, finds explanations in unstructured documents through semantic search, and combines both into a grounded answer.
From IBM Technology — What Is a Digital Librarian AI Agent? Connecting SQL & Vector Database at 01:37
Problem: Important answers are split between SQL databases containing facts and unstructured documents containing explanations, making it difficult for people to understand not only what happened but why.
For: Organizations in industries with siloed structured and unstructured data, including pharmacies and other businesses that need answers combining records with policies, rules, or supporting documents.
Products from this video
Examples
- Prescription-coverage assistant: combines a SQL result showing whether a drug is covered with a policy-manual passage explaining why it is or is not covered.