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Teams that rely on dashboards for daily decisions often must pinch and zoom to interact with controls originally designed for larger displays. Checking revenue during a morning standup, reviewing pipeline metrics between meetings, or monitoring operations while traveling all require extra effort when the dashboard was built for a desktop screen. Mobile Layout for Amazon […]

Smartsheet is an enterprise work management platform that hundreds of thousands of organizations rely on. As enterprise teams adopt AI agents, those agents need structured access to the data inside systems like Smartsheet, but most systems aren’t built for that. To bridge this gap, Smartsheet built a remote Model Context Protocol (MCP) server on AWS

Knowledge bases that ground agents and generative AI applications over your enterprise data are hard to build at scale. Teams typically stitch together connectors, parsers, vector stores, knowledge graphs, and retrieval logic, then operationalize all of it for production. Each piece brings its own challenges. You must decide which data sources to connect and how

This post is co-written with Eric Jiang from xAI (SpaceXAI). xAI’s Grok 4.3 is now generally available on Amazon Bedrock, giving teams that build agents and AI workflows a model that reasons reliably over long inputs. With this launch, xAI joins Amazon Bedrock as a model provider. Grok 4.3 is a model with configurable reasoning

Gemini Omni and personal avatars in Google Vids make video creation easier than ever. ​ 

You’ll be able to securely link and interact with your go-to services directly in AI Mode. ​ 

Restaurants miss an average of 150 phone calls per location every month, and about 60 percent of those are customers trying to place an order or book a table. Most of these calls come in during dinner service, exactly when the host is seating guests, servers are turning tables, and the phone becomes an afterthought.

Document processing in real estate is complex and highly manual, impacting critical business decisions at scale, making it ripe for automation. Built Technologies, a real estate finance software provider, processes over $500B in real estate projects. The company deployed an AI-powered document processing engine on Amazon Bedrock and the AWS Intelligent Document Processing (IDP) Accelerator.

The integration of AI into real-world applications has long been hindered by a fundamental challenge: the disconnect between systems that can see, systems that can think, and systems that can act. Developers have struggled with complex integrations, managing multiple APIs, and creating custom solutions to bridge these gaps, resulting in inefficient, costly, and often fragile

Using Amazon SageMaker Pipelines, organizations can automate their machine learning (ML) workloads and distribute them over many AWS accounts and AWS Regions as part of their Machine Learning Operations (MLOps) strategy. However, monitoring SageMaker Pipelines can become complex when they are distributed across many AWS environments. Developers and operations engineers must manually switch between multiple