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Manufacturing intelligence with Amazon Nova Multimodal Embeddings
In this post, we build a multimodal retrieval system for aerospace manufacturing documents using Amazon Nova Multimodal Embeddings on Amazon Bedrock and Amazon S3 Vectors. We evaluate the system on 26 manufacturing queries and compare generation quality between a text-only pipeline and the multimodal pipeline.
How Miro uses Amazon Bedrock to boost software bug routing accuracy and improve time-to-resolution from days to hours
In this post, we dive deep into the architecture and techniques we used to improve Miro’s bug routing, achieving six times fewer team reassignments and five times shorter time-to-resolution powered by Amazon Bedrock.
Amazon Quick: Accelerating the path from enterprise data to AI-powered decisions
Amazon Quick helps turn your large enterprise data into fast and accurate AI-powered decisions. In this post, you will learn about five new capabilities of Amazon Quick that accelerate how data professionals deliver trusted AI-powered insights at enterprise scale.
AWS Transform now automates BI migration to Amazon Quick in days
In this post, we walk through the full journey, from setting up your migration workspace in AWS Transform to subscribing to partner agents through AWS Marketplace to unlocking Amazon Quick capabilities that change how your organization consumes data.
AWS Generative AI Model Agility Solution: A comprehensive guide to migrating LLMs for generative AI production
In this post, we introduce a systematic framework for LLM migration or upgrade in generative AI production, encompassing essential tools, methodologies, and best practices. The framework facilitates transitions between different LLMs by providing robust protocols for prompt conversion and optimization.
Sun Finance automates ID extraction and fraud detection with generative AI on AWS
In this post, we show how Sun Finance used Amazon Bedrock, Amazon Textract, and Amazon Rekognition to build an AI-powered identity verification (IDV) pipeline. The solution improved extraction accuracy from 79.7% to 90.8%, cut per-document costs by 91%, and reduced processing time from up to 20 hours to under 5 seconds. You'll learn how combining specialized OCR with large language model (LLM) structuring outperformed using either tool alone. You'll also learn how to architect a serverless fraud detection system using vector similarity search.
Unleashing Agentic AI Analytics on Amazon SageMaker with Amazon Athena and Amazon Quick
This post demonstrates how agentic AI assistant from Amazon Quick transform data analytics into a self-service capability by using Amazon Simple Storage Service (Amazon S3) as a storage, Amazon SageMaker and AWS Glue for lakehouse, Amazon Athena for serverless SQL querying across multiple storage formats (S3 Table, Iceberg, and Parquet).
Configuring Amazon Bedrock AgentCore Gateway for secure access to private resources
In this post, you will configure Amazon Bedrock AgentCore Gateway to access private endpoints using Resource Gateway, a managed construct that provisions Elastic Network Interfaces (ENIs) directly inside your Amazon VPC, one per subnet. You will explore two implementation modes (managed and self-managed) and walk through three practical scenarios: connecting to a private Amazon API Gateway endpoint, integrating with a MCP server on Amazon Elastic Kubernetes Service (Amazon EKS), and accessing a private REST API.
[AINews] The Inference Inflection
a quiet day lets us reflect on the growing implications of the inference age
Extracting contract insights with PwC’s AI-driven annotation on AWS
This post was co-written with Yash Munsadwala, Adam Hood, Justin Guse, and Hector Hernandez from PwC. Contract analysis often consumes significant time for legal, compliance, and procurement teams, especially when important insights are buried in lengthy, unstructured agreements. As contract volumes grow, finding specific clauses and assessing extracted terms can become increasingly difficult to scale. […]
Organizing Agents’ memory at scale: Namespace design patterns in AgentCore Memory
In this post, you will learn how to design namespace hierarchies, choose the right retrieval patterns, and implement AWS Identity and Access Management (IAM)-based access control for AgentCore Memory.
Building AI-ready data: Vanguard’s Virtual Analyst journey
In this post, you'll learn how Vanguard built their Virtual Analyst solution by focusing on eight guiding principles of AI-ready data, the AWS services that powered their implementation, and the measurable business outcomes they achieved.
Run custom MCP proxies serverless on Amazon Bedrock AgentCore Runtime
This post shows you how to deploy a serverless MCP proxy on Amazon Bedrock AgentCore Runtime that gives you a programmable layer to implement proper governance, controls, and observability aligned with an organization's security policies.
Amazon Quick for marketing: From scattered data to strategic action
Amazon Quick changes how you work. You can set it up in minutes and by the end of the day, you will wonder how you ever worked without it. Quick connects with your applications, tools, and data, creating a personal knowledge graph that learns your priorities, preferences, and network.
Applying multimodal biological foundation models across therapeutics and patient care
In this post, we'll explore how multimodal BioFMs work, showcase real-world applications in drug discovery and clinical development, and contextualize how AWS enables organizations to build and deploy multimodal BioFMs.
Cost-effective multilingual audio transcription at scale with Parakeet-TDT and AWS Batch
In this post, we walk through building a scalable, event-driven transcription pipeline that automatically processes audio files uploaded to Amazon Simple Storage Service (Amazon S3), and show you how to use Amazon EC2 Spot Instances and buffered streaming inference to further reduce costs.
Amazon SageMaker AI now supports optimized generative AI inference recommendations
Today, Amazon SageMaker AInbsp; supports optimized generative AI inference recommendations. By delivering validated, optimal deployment configurations with performance metrics, Amazon SageMaker AI keeps your model developers focused on building accurate models, not managing infrastructure.
Get to your first working agent in minutes: Announcing new features in Amazon Bedrock AgentCore
Today, we're introducing new capabilities that further streamline the agent building experience, removing the infrastructure barriers that slow teams down at every stage of agent development from the first prototype through production deployment.
Company-wise memory in Amazon Bedrock with Amazon Neptune and Mem0
Company-wise memory in Amazon Bedrock, powered by Amazon Neptune and Mem0, provides AI agents with persistent, company-specific context—enabling them to learn, adapt, and respond intelligently across multiple interactions. TrendMicro, one of the largest antivirus software companies in the world, developed the Trend’s Companion chatbot, so their customers can explore information through natural, conversational interactions
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