12/8/2025, 12:00:00 AM ~ 12/9/2025, 12:00:00 AM (UTC)
Recent Announcements
Amazon Quick Suite integrates Quick Research with Quick Flows for report automation
Amazon Quick Suite now includes Quick Research as a step within Quick Flows. This integration enables teams to generate comprehensive research reports as part of automated, multi-step workflows, transforming research projects into reusable workflows that can be shared across their organization.\n Quick Suite is Amazon’s new AI-powered workspace that helps organizations get answers from their business data and move quickly from insights to action. With this integration, teams can trigger research automatically within their flows rather than conducting separate analysis. This addresses a critical productivity challenge by enabling teams to capture and scale proven research methods across hundreds of automated use cases. The integration also allows users to automate research workflows through scheduled triggers so users can set up flows that automatically generate research at specific times. Common use cases include automated account plan creation, standardizing product compliance analysis, and scheduled industry reports. Users benefit from pre-configured flows that generate research based on flow creator instructions and optional user inputs. The generated research report can be used further to automatically trigger downstream actions like updating a Salesforce opportunity for an account team to follow up on, posting on a Jira ticket for a compliance team to review, or creating an Asana task for a patent lawyer to approve. This unlocks “set and forget” workflows that deliver consistent analysis without manual heavy lifting. Now operating within these automated workflows, Quick Research maintains its core strength of streamlining analysis across diverse enterprise data sources while delivering verified, source-traced insights. For existing Flow users, this provides access to more comprehensive analysis. Quick Research with Flows integration is available in the following AWS Regions: US East (N. Virginia), US West (Oregon), Asia Pacific (Sydney), and Europe (Ireland). To learn more about automating your research needs, read the Quick Suite user guide.
Announcing Spatial Data Management on AWS to accelerate spatial-data insights
Today, AWS is announcing Spatial Data Management on AWS (SDMA), a solution that enables customers to store, enrich, and connect spatial data at scale. SDMA enables customers to store their multimodal spatial data representing their physical assets (3D, geospatial, behavioral, temporal data) in a secure, centralized cloud environment. SDMA serves as a collaborative hub enabling connectivity between customer’s spatial data, their ISV SaaS applications, and AWS Services. In addition, customers can use SDMA’s collection rules to define how their spatial data is organized and enriched, helping maintain consistency and governance. Customers can use SDMA’s APIs, desktop application, and web interface to efficiently manage spatial data to accelerate insights and informed decision making around physical operations.\n SDMA centralizes customer’s spatial data in a secure and highly available cloud repository to enhance data transparency and accessibility across workflows. Leveraging SDMA’s automated metadata extraction for spatial data file formats, starting with: .LAZ, .E57, .GLB, and .GLTF, customers can improve data discoverability and relationships. SDMA’s REST APIs and customizable connectors simplify integrations with external applications — eliminating manual file handling and enhancing cloud and on-premises interoperability. SDMA’s intuitive web and desktop interfaces enable users across technical skill levels to manage spatial data efficiently. Auto-generated file previews are designed to improve workflow speed and data accuracy, they allow users to view and validate data without downloading large files.
SDMA is available in the following AWS regions: Asia Pacific (Tokyo, Singapore, Sydney), Europe (Frankfurt, Ireland, London), US East (N. Virginia, Ohio), US West (Oregon).
To learn more, visit the SDMA Product page.
YouTube
AWS Black Belt Online Seminar (Japanese)
- AWS Security Hub CSPM [AWS Black Belt]
- AWS CodePipeline Basic Edition [AWS Black Belt]
- Overview of Amazon Elastic VMware Service [AWS Black Belt]
- Amazon EC2 instance options I can’t hear now [AWS Black Belt]
AWS Blogs
AWS Japan Blog (Japanese)
- Introducing the AWS Transform Discovery Tool
- Deciphering the Future of Retail: Using AI Shopping Agents
- A guide for the retail and consumer goods industry in re:Invent 2025
- Weekly Generative AI with AWS — Re:Invent 2025 Special Issue Part 1 (2025/12/8 week)
- Amazon SageMaker AI’s new serverless customizations accelerate model fine-tuning
- Weekly AWS — Re:Invent 2025 Special Issue Part 3 (2025/12/8 week)
- Amazon Bedrock has added fine-tuning through reinforcement learning to simplify how developers build smarter and more accurate AI models
- Weekly AWS — Re:Invent 2025 Special Issue Part 2 (2025/12/8 week)
- Introducing elastic training without checkpoints on Amazon SageMaker HyperPod
AWS News Blog
AWS Architecture Blog
AWS Big Data Blog
- Auto-optimize your Amazon OpenSearch Service vector database
- Build billion-scale vector databases in under an hour with GPU acceleration on Amazon OpenSearch Service
- SAP data ingestion and replication with AWS Glue zero-ETL
AWS Database Blog
AWS Developer Tools Blog
Artificial Intelligence
- How AWS delivers generative AI to the public sector in weeks, not years
- S&P Global Data integration expands Amazon Quick Research capabilities
- Streamline AI agent tool interactions: Connect API Gateway to AgentCore Gateway with MCP
- Create an intelligent insurance underwriter agent powered by Amazon Nova 2 Lite and Amazon Quick Suite
Networking & Content Delivery
AWS Security Blog
- IAM Policy Autopilot: An open-source tool that brings IAM policy expertise to builders and AI coding assistants
- AWS launches AI-enhanced security innovations at re:Invent 2025