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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. …

Extracting contract insights with PwC’s AI-driven annotation on AWS Read More »

When building AI agents, developers struggle with organizing memory across sessions, which leads to irrelevant context retrieval and security vulnerabilities. AI agents that remember context across sessions need more than only storage. They need organized, retrievable, and secure memory. In Amazon Bedrock AgentCore Memory, namespaces determine how long-term memory records are organized, retrieved, and who …

Organizing Agents’ memory at scale: Namespace design patterns in AgentCore Memory Read More »

Vanguard is a global investment management firm, offering a broad selection of investments, advice, retirement services, and insights to individual investors, institutions, and financial professionals. We operate under a unique, investor-owned structure and adhere to a straightforward purpose: To take a stand for all investors, to treat them fairly, and to give them the best …

Building AI-ready data: Vanguard’s Virtual Analyst journey Read More »

When AI agents connect to tools through the Model Context Protocol (MCP), they gain access to capabilities that range from database queries and API calls to file operations and third-party service integrations. In production, these interactions need proper governance, controls, and observability aligned with an organization’s security policies. This includes sanitizing tool inputs before they …

Run custom MCP proxies serverless on Amazon Bedrock AgentCore Runtime Read More »

Migrating a text agent to a voice assistant is increasingly important because users expect faster, more natural interactions. Instead of typing, customers want to speak and understand in real time. Industries like finance, healthcare, education, social media, and retail are exploring solutions with Amazon Nova 2 Sonic to enable natural, real-time speech interactions at scale. …

Migrating a text agent to a voice assistant with Amazon Nova 2 Sonic Read More »

Today, we are excited to announce the day zero availability of NVIDIA Nemotron 3 Nano Omni on Amazon SageMaker JumpStart. This multimodal model from NVIDIA combines video, audio, image, and text understanding into a single, efficient architecture, enabling enterprise customers to build intelligent applications that can see, hear, and reason across modalities in one inference …

NVIDIA Nemotron 3 Nano Omni model now available on Amazon SageMaker JumpStart Read More »

Google’s sharing 20 fun facts to celebrate Google Translate turning 20, from its roots as a 2006 AI experiment to supporting almost 250 languages today. ​ 

Consider a typical Monday morning: you’re manually copying data from several different systems to create a weekly report, then formatting it for different stakeholders. This single task can consume several hours that could be spent on more strategic work. Multiply this across your team, and these repetitive tasks add up quickly. Amazon Quick Flows automates these …

Automate repetitive tasks with Amazon Quick Flows Read More »

With Amazon Bedrock Knowledge Bases, you can give foundation models (FMs) and agents contextual information from your organization’s private data sources to deliver more relevant, accurate, and customized responses. As the data grows, maintaining real-time synchronization between Amazon Simple Storage Service (Amazon S3) and your knowledge bases becomes critical for accurate, up-to-date responses.In this post, …

Build and deploy an automatic sync solution for Amazon Bedrock Knowledge Bases Read More »

Enterprises building AI agents often require more than what managed foundation model (FM) services can provide. They need precise control over performance tuning, cost optimization at scale, compliance and data residency, model selection, and networking configurations that integrate with existing security architectures. Amazon SageMaker AI endpoints align with these requirements by giving organizations control over …

Build Strands Agents with SageMaker AI models and MLflow Read More »