Category: Artificial Intelligence

In this post, we share how we applied Amazon Bedrock and the Amazon Nova family of models to reimagine our Title Suggestion feature. By combining metadata, computer vision, and retrieval-augmented generative AI, we now automatically generate creative, brand-aligned titles and subtitles across 12 languages. Using the unified API of Amazon Bedrock, Anthropic’s Claude 3 Haiku, and Amazon Nova Lite and Pro, we improved quality, reduced cost, and cut response times. This resulted in higher customer satisfaction, measurable uplifts in engagement and purchase rates, and over 5.5 million personalised titles generated in 2025.

In this post, we show how connecting the Visier Workforce AI platform with Amazon Quick through Model Context Protocol (MCP) gives every knowledge worker a unified agentic workspace to ask questions in. Visier helps ground the workspace in live workforce data and the organizational context that surrounds it while letting your users act on the conversational results without switching tools.

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.

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.

Today, Amazon SageMaker AI  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.

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, 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

Today, we’re excited to announce Claude Cowork in Amazon Bedrock. You can now run Cowork and Claude Code Desktop through Amazon Bedrock, directly or using an LLM gateway. In this post, we walk through how Claude Cowork integrates with Amazon Bedrock and show an example of how knowledge workers use it in practice.

In this post, we show how to combine DVC (Data Version Control), Amazon SageMaker AI, and Amazon SageMaker AI MLflow Apps to build end-to-end ML model lineage. We walk through two deployable patterns — dataset-level lineage and record-level lineage — that you can run in your own AWS account using the companion notebooks.

Today, we are thrilled to announce the availability of G7e instances powered by NVIDIA RTX PRO 6000 Blackwell Server Edition GPUs on Amazon SageMaker AI. You can provision nodes with 1, 2, 4, and 8 RTX PRO 6000 GPU instances, with each GPU providing 96 GB of GDDR7 memory. This launch provides the capability to use a single-node GPU, G7e.2xlarge instance to host powerful open source foundation models (FMs) like GPT-OSS-120B, Nemotron-3-Super-120B-A12B (NVFP4 variant), and Qwen3.5-35B-A3B, offering organizations a cost-effective and high-performing option.