Hybrid Geospatial RAG with Elasticsearch and Amazon Bedrock

AI Impact Summary

This blog post details a RAG application leveraging Elasticsearch, Amazon Bedrock, and LangChain for real estate property recommendations. The system utilizes Elasticsearch's vector database and geospatial capabilities to perform hybrid searches combining lexical and geospatial queries, alongside LLM-powered generation. The architecture involves geocoding user queries via Amazon Location Service, querying Elasticsearch with a combined keyword and distance search, and then feeding the results to Amazon Bedrock’s Claude 3 Sonnet for generating a summary, demonstrating a robust and scalable approach to location-based AI.