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Here are 12 of the biggest Google I/O 2026 keynote moments, including news about Gemini Omni, Gemini 3.5 Flash and more. ​ 

Financial institutions process thousands of documents daily, including tax forms, loan statements, and purchase orders. Each has a unique format, structure, and field names, making it challenging to create automation workflows using optical character recognition (OCR) software. Amazon Bedrock Data Automation (BDA) helps solve these challenges by automating the extraction, validation, and analysis of data

Developing AI agents for business support presents unique challenges that many organizations face when trying to automate routine HR tasks. Works Human Intelligence (WHI) develops, sells, and supports the integrated HR system “COMPANY” for major Japanese corporations and public interest corporations. In this post, we share how the AWS Generative AI Innovation Center (GenAIIC) collaborated

A special thanks goes to the Verizon Connect team who’s been working very hard on the project: Matteo Simoncini, Luca Bravi, Alberto Rossettini, Martin Villarruel, Ceyhun Unlu, Adriel Zuquini, Andrea Benericetti. Fleet managers today face an overwhelming challenge: transforming data overload into actionable insights. When you’re managing thousands of vehicles, each generating hundreds of daily

AWS leaders manage complex data across multiple hierarchies while making time-sensitive decisions that impact global operations. Traditional business intelligence relies on static dashboards and manual reports, which creates delays and limits organizational agility. NarrateAI, our intelligent conversational solution, addresses this through conversational agentic AI powered by our data lake and Amazon Bedrock AgentCore. Accessible through

As agent adoption scaled, we saw a common pattern emerge across enterprises, including our own sales organization: specialized agents deliver value, but without orchestration, users carry the cognitive load of choosing between them. At AWS Sales, this meant more than 20 domain-specific agents deployed across the global organization, with representatives context-switching between systems instead of

The industry is entering a world where billions of generative AI agents operate autonomously, acting on behalf of humans, making decisions, and completing tasks without human intervention. To support this shift, Amazon Bedrock AgentCore provides a modular, fully managed platform that helps developers build, deploy, and operate generative AI agents at scale. By abstracting the

Generative AI has rapidly evolved from experimental prototypes into systems that are expected to operate reliably in production, at scale, and under real-world performance constraints. As organizations move beyond demos and proofs of concept, they increasingly encounter challenges related to inference latency, scalability, state management, and operational visibility. Building high-performance AI agents today requires more

Building high-performance generative AI agents requires architecture that can deliver fast inference, coordinate multiple agents, and operate reliably under production workloads. If you are building generative AI agents to automate reviews, power digital assistants, and support complex decision-making workflows, you need these agents to perform well. They must reduce manual effort, respond in near real

AgentWatch delivers ambient AWS resource monitoring for your DevOps team, moving beyond the reactive cycle of managing Amazon CloudWatch alarms across multiple accounts. CloudWatch alarms trigger too late, AWS Lambda errors accumulate unnoticed, and Amazon Elastic Compute Cloud (Amazon EC2) performance degradation goes undetected until customers report problems. This leaves your team constantly firefighting rather