Releases·Tool Release
Amazon Bedrock Knowledge Bases builds a cited claims Q&A assistant using agentic retrieval and metadata filters
AWS published a technical how-to for building an insurance claims assistant on Amazon Bedrock Knowledge Bases, using agentic retrieval to answer natural-language questions over claim documents with citations. The guide combines S3-indexed claim files, metadata filtering, Guardrails grounding checks, and multi-turn conversation. A 40-question evaluation on synthetic data showed 90.5% retrieval recall and 81.2% citation recall.
0 engagement1 sourceWed, Sep 30, 2026, 03:37 PM
AI Overview
- AWS technical guide builds a claims assistant on Amazon Bedrock Knowledge Bases using AgenticRetrieveStream to break questions into sub-queries and return citations
- Setup uses S3 documents with .metadata. sidecars (10 KB limit) filtering on claim_id, status, amount, region, and has_subrogation; dates stored as YYYYMMDD integers
- On a 40-question synthetic suite, Retrieve and RetrieveAndGenerate achieved 90.5% retrieval recall, 81.2% citation recall, and 3.9 citations per answer
- On 20 adversarial questions, retrieval recall reached 96.7% and citation recall 90.2%, separating similarly named companies and ignoring instruction-like document text
- Guide advises deriving access-control filters from the authenticated session server-side, never from user text, with CloudTrail logging and TLS for API traffic
Related
Releases·Tool Release
AWS showcases agentic retrieval with LangChain on Amazon Bedrock Managed Knowledge Bases
An AWS engineering post demonstrates agentic retrieval on Amazon Bedrock Managed Knowledge Bases via the langchain-aws package, contrasting it with standard single-shot Retrieve for multi-part RAG questions. A test question containing six intents was only partially covered by similarity search at five chunks, while the agentic planning loop decomposes the question into sub-queries and iterates until evidence is sufficient. It matters to practitioners choosing between cheaper single-shot retrieval and costlier agentic retrieval.
An AWS engineering post demonstrates agentic retrieval on Amazon Bedrock Managed Knowledge Bases via the langchain-aws package, contrasting it with standard single-shot Retrieve for multi-part RAG questions. A test question containing six intents was only partially covered by similarity search at five chunks, while the agentic planning loop decomposes the question into sub-queries and iterates until evidence is sufficient. It matters to practitioners choosing between cheaper single-shot retrieval and costlier agentic retrieval.
0 engagement1 sourcerssMon, Oct 5, 2026, 03:53 PM
Social·Community
Builder writes guide to production-grade RAG on Amazon Bedrock, covering Knowledge Bases, chunking, and evaluation
A developer posted a practical guide on building reliable RAG applications on AWS using Amazon Bedrock, shared on Reddit for community feedback. The guide emphasizes engineering considerations for production—retrieval quality, chunking, evaluation—over introductory explanations, making it a practitioner-focused resource for teams building on AWS.
A developer posted a practical guide on building reliable RAG applications on AWS using Amazon Bedrock, shared on Reddit for community feedback. The guide emphasizes engineering considerations for production—retrieval quality, chunking, evaluation—over introductory explanations, making it a practitioner-focused resource for teams building on AWS.
7 engagement1 sourceredditThu, Oct 8, 2026, 07:00 AM
Releases·Tool Release
AWS publishes patterns for observable and multi-tenant agentic retrieval on Amazon Bedrock Knowledge Bases
AWS published two posts on building agentic retrieval with Managed Amazon Bedrock Knowledge Bases: one on observability for enterprise agentic retrieval using AWS CloudFormation, and one on multi-tenant agentic chat over enterprise data. Both target the step beyond single-source RAG, where an agent routes questions across knowledge bases and retrieves iteratively. The multi-tenant post emphasizes per-tenant document isolation enforced from verified identity rather than client-supplied values.
AWS published two posts on building agentic retrieval with Managed Amazon Bedrock Knowledge Bases: one on observability for enterprise agentic retrieval using AWS CloudFormation, and one on multi-tenant agentic chat over enterprise data. Both target the step beyond single-source RAG, where an agent routes questions across knowledge bases and retrieves iteratively. The multi-tenant post emphasizes per-tenant document isolation enforced from verified identity rather than client-supplied values.
0 engagement2 sourcesrssMon, Aug 31, 2026, 06:56 PM
Releases·Tool Release
AWS benchmarks OpenSearch Serverless configs for Bedrock Knowledge Bases RAG vector store selection
An AWS Machine Learning blog post guides builders choosing a customer-managed vector store for Amazon Bedrock Knowledge Bases, comparing Amazon OpenSearch Service, Amazon Aurora PostgreSQL with pgvector, and Amazon S3 Vectors across three RAG use cases. It includes original benchmarks on OpenSearch Serverless Classic collections using Amazon's ESCI shopping dataset, measuring NDCG@10, latency, and index size across embedding dimension and data type configurations. The guidance helps practitioners trade off latency, cost, and search quality when building RAG on AWS.
An AWS Machine Learning blog post guides builders choosing a customer-managed vector store for Amazon Bedrock Knowledge Bases, comparing Amazon OpenSearch Service, Amazon Aurora PostgreSQL with pgvector, and Amazon S3 Vectors across three RAG use cases. It includes original benchmarks on OpenSearch Serverless Classic collections using Amazon's ESCI shopping dataset, measuring NDCG@10, latency, and index size across embedding dimension and data type configurations. The guidance helps practitioners trade off latency, cost, and search quality when building RAG on AWS.
0 engagement1 sourcerssThu, Sep 17, 2026, 03:53 PM
Releases·Tool Release
AWS shows connecting Bedrock AgentCore to cross-account knowledge bases
AWS published a guide explaining how to connect Amazon Bedrock AgentCore agents to knowledge bases hosted in separate AWS accounts, using Amazon Bedrock Knowledge Bases backed by Amazon Redshift Serverless. The post addresses integration challenges from cross-account separation and provides a solution for maintaining workload boundaries.
AWS published a guide explaining how to connect Amazon Bedrock AgentCore agents to knowledge bases hosted in separate AWS accounts, using Amazon Bedrock Knowledge Bases backed by Amazon Redshift Serverless. The post addresses integration challenges from cross-account separation and provides a solution for maintaining workload boundaries.
0 engagement1 sourcerssWed, Aug 26, 2026, 03:48 PM