Search enterprise data assets using LLMs backed by knowledge graphs
Machine Learning Blog
This article demonstrates a solution for searching enterprise data assets using Large Language Models (LLMs) and knowledge graphs, specifically leveraging AWS services like Amazon Bedrock, Amazon Neptune, and Amazon DataZone.
- Solution integrates metadata from multiple data sources into a unified semantic search platform
- Uses knowledge graphs to provide reasoning and context for search results
- Enables natural language queries across enterprise data assets
- Utilizes AWS services including Step Functions, Lambda, Neptune, and Bedrock
- Provides a Streamlit-based chatbot UI for querying data assets
The solution combines LLMs' natural language processing with knowledge graphs' structured reasoning to create a powerful, context-aware enterprise search tool that can unlock insights across fragmented data sources.
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