aws-samples/amazon-bedrock-rag
Fully managed RAG solution implemented using Knowledge Bases for Amazon Bedrock
This project helps you build a custom chatbot that can answer questions using your own private documents or website content. You provide your proprietary information, and the chatbot generates accurate answers, citing its sources from your data, instead of relying solely on generic internet knowledge. This is ideal for knowledge managers, customer support leads, or anyone needing to make internal company data or specific domain knowledge easily searchable and consumable through a conversational AI.
195 stars.
Use this if you need to create a secure, fully-managed AI chatbot that provides answers based on your internal company documents or specific website content, without needing to retrain large language models.
Not ideal if you're looking for a simple, pre-built chatbot without specific domain knowledge or if you prefer to manually manage all the underlying infrastructure.
Stars
195
Forks
52
Language
JavaScript
License
MIT-0
Category
Last pushed
Mar 05, 2026
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/rag/aws-samples/amazon-bedrock-rag"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Compare
Related tools
aws-samples/generative-ai-use-cases
Application implementation with business use cases for safely utilizing generative AI in...
aws-samples/serverless-rag-demo
Amazon Bedrock Foundation models with Amazon Opensearch Serverless as a Vector DB
IBM/granite-workshop
Source code for the IBM Granite AI Model Workshop
aws-samples/rag-with-amazon-bedrock-and-opensearch
Opinionated sample on how to build and deploy a RAG application with Amazon Bedrock and OpenSearch
aws-samples/generative-bi-using-rag
A solution guidance for Generative BI using Amazon Bedrock, Amazon OpenSearch with RAG