Amazon Bedrock Knowledge Bases

2026-11-02

CODING · 1 SOURCE · AWS Machine Learning

Amazon outlines Crawl4AI workflow to prepare web content for Bedrock Knowledge Bases

AWS published a how‑to showing a sample workflow that uses the open‑source Crawl4AI crawler to generate Markdown plus metadata sidecars uploaded to Amazon S3 for ingestion by Amazon Bedrock Knowledge Bases. The post explains when to use the built‑in Bedrock Web Crawler versus Crawl4AI for targeted extraction, custom metadata, and boilerplate pruning, and links an aws‑samples repo with the implementation using EventBridge, ECS/Fargate, and S3.

6.0

2026-11-02

COMPANIES · 1 SOURCE · AWS Machine Learning

Circle K automates DevOps triage with Amazon Bedrock, cuts mean time to triage to under 15 minutes

Circle K built an automated, agentic triage system on Amazon Bedrock (initially with Bedrock Flows, later migrated to Bedrock AgentCore) that queries logs, services, and internal runbooks and posts structured summaries to Slack; the team reports mean triage time fell to under 15 minutes (a 67–75% reduction by their metrics). The implementation used managed Bedrock features (Agents/AgentCore and Bedrock Knowledge Bases for RAG) to avoid self-hosting models and orchestration code.

6.0

2026-10-14

CODING · 1 SOURCE · AWS Machine Learning

Amazon Bedrock AgentCore demo automates PowerPoint creation using Claude Sonnet 4.6

AWS published a how-to showing an AI agent system built on Amazon Bedrock AgentCore that automates generating client PowerPoint presentations from enterprise documents. The solution uses a supervisor agent (AgentCore runtime + Strands Agents) with Anthropic Claude Sonnet 4.6 for content, Amazon Titan Text Embeddings v2 and Amazon OpenSearch Serverless for RAG vector search, Stability AI Stable Image Inpaint for images, a .NET 8 REST API and AWS Lambda for generation, and a public code repository; internal testing completed in under 90 seconds.

6.0

2026-10-07

COMPANIES · 1 SOURCE · AWS Machine Learning

Amazon adds real-time ACL verification to Quick and Bedrock Knowledge Bases for RAG

Amazon implemented a two-stage access-control approach for Amazon Quick and Amazon Bedrock Knowledge Bases: pre-retrieval ACL filtering against indexed attributes, followed by real-time verification with authoritative data sources (e.g., Google Drive APIs using service-account impersonation) to ensure RAG responses respect current permissions.

6.0

2026-10-06

COMPANIES · 1 SOURCE · AWS Machine Learning

AWS publishes tutorial to build a voice travel concierge with Bedrock AgentCore and Nova 2.5 Sonic

AWS published a how-to demonstrating a voice travel concierge built with Amazon Bedrock AgentCore (runtime and Gateway), Amazon Nova 2.5 Sonic for real‑time speech, and Amazon Bedrock Knowledge Bases, using the AWS CDK and the Model Context Protocol (MCP) to connect the agent to backend services. The post details architecture, components (authentication, data stores, Lambdas, API Gateway), and a sample airline implementation that keeps the agent loosely coupled to existing systems.

5.0

2026-09-30

CODING · 1 SOURCE · AWS Machine Learning

AWS how-to: build a cited-answers claims assistant with Amazon Bedrock Knowledge Bases

AWS published a technical how‑to showing how to index claim documents from Amazon S3 into Amazon Bedrock Knowledge Bases and use the AgenticRetrieveStream API to answer natural‑language questions with streamed trace events, citations, and grounding checks; the walkthrough uses synthetic claim records and demonstrates scoping via metadata filters and a contextual grounding guardrail. The guide explains ingestion (parsing, chunking, embeddings, vector storage), agentic retrieval that iterates sub-queries, and streaming of answers, traces, and citations to support auditable, source-backed responses.

6.0

2026-09-24

COMPANIES · 1 SOURCE · AWS Machine Learning

Amazon Bedrock: multi-account AI agent architecture using AgentCore Gateway and MCP

Amazon’s post describes a reference architecture for building multi-account AI agents that query data in-place across multiple AWS line-of-business (LOB) accounts without centralizing datasets. It shows how a central platform account can host agents and Bedrock inference while AgentCore Gateway (with MCP, AgentCore Identity, Policy in AgentCore/Cedar, and optional Okta auth) aggregates LOB MCP servers, provides unified tool discovery, authorization, observability, and applies Bedrock guardrails and RAG-backed knowledge retrieval.

6.0

2026-09-17

COMPANIES · 1 SOURCE · AWS Machine Learning

AWS outlines vector-store choices for Amazon Bedrock Knowledge Bases (OpenSearch, Aurora pgvector, S3 Vectors)

AWS published guidance for the customer-managed configuration of Amazon Bedrock Knowledge Bases, comparing three supported vector-store backends—Amazon OpenSearch Service (managed and serverless), Amazon Aurora PostgreSQL with pgvector, and Amazon S3 Vectors—and evaluating their tradeoffs across RAG use cases (latency, cost, scalability). The post maps each backend to example workloads such as e-commerce product search and discusses performance and cost implications.

6.0

2026-09-10

MODELS · 1 SOURCE · AWS Machine Learning

TwelveLabs' Marengo Embed 3.0 added to Amazon Bedrock Knowledge Bases for video, image and audio search

TwelveLabs' Marengo Embed 3.0 is now generally available as an embedding model in Amazon Bedrock Knowledge Bases, enabling fully managed natural-language semantic search over video, image and audio content. AWS Machine Learning published a walkthrough showing how to build a Bedrock knowledge base powered by Marengo 3.0 and run semantic queries against media.

6.0