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AI agents at work: The new frontier in business automation

AI agents at work: The new frontier in business automation

Microsoft’s AI agents are at the forefront of a significant transformation in modern business operations. These intelligent agents automate routine tasks, helping employees by freeing up valuable time to be more efficient, productive, and empowered to drive business—and industries are discovering their value. Across sectors such as finance, healthcare, and manufacturing, AI agents handle tasks …

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Amazon Q Business simplifies integration of enterprise knowledge bases at scale

Amazon Q Business simplifies integration of enterprise knowledge bases at scale

In this new era of emerging AI technologies, we have the opportunity to build AI-powered assistants tailored to specific business requirements. Amazon Q Business, a new generative AI-powered assistant, can answer questions, provide summaries, generate content, and securely complete tasks based on data and information in an enterprise’s systems. Large-scale data ingestion is crucial for …

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Faster distributed graph neural network training with GraphStorm v0.4

Faster distributed graph neural network training with GraphStorm v0.4

GraphStorm is a low-code enterprise graph machine learning (ML) framework that provides ML practitioners a simple way of building, training, and deploying graph ML solutions on industry-scale graph data. Although GraphStorm can run efficiently on single instances for small graphs, it truly shines when scaling to enterprise-level graphs in distributed mode using a cluster of …

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Transforming credit decisions using generative AI with Rich Data Co and AWS

Transforming credit decisions using generative AI with Rich Data Co and AWS

This post is co-written with Gordon Campbell, Charles Guan, and Hendra Suryanto from RDC.  The mission of Rich Data Co (RDC) is to broaden access to sustainable credit globally. Its software-as-a-service (SaaS) solution empowers leading banks and lenders with deep customer insights and AI-driven decision-making capabilities. Making credit decisions using AI can be challenging, requiring …

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Build agentic AI solutions with DeepSeek-R1, CrewAI, and Amazon SageMaker AI

Build agentic AI solutions with DeepSeek-R1, CrewAI, and Amazon SageMaker AI

AI agents are rapidly becoming the next frontier in enterprise transformation, with 82% of organizations planning adoption within the next 3 years. According to a Capgemini survey of 1,100 executives at large enterprises, 10% of organizations already use AI agents, and more than half plan to use them in the next year. The recent release …

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Automate bulk image editing with Crop.photo and Amazon Rekognition

Automate bulk image editing with Crop.photo and Amazon Rekognition

Evolphin Software, Inc. is a leading provider of digital and media asset management solutions based in Silicon Valley, California. Crop.photo from Evolphin Software is a cloud-based service that offers powerful bulk processing tools for automating image cropping, content resizing, background removal, and listing image analysis. Crop.photo is tailored for high-end retailers, ecommerce platforms, and sports …

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Revolutionizing business processes with Amazon Bedrock and Appian’s generative AI skills

Revolutionizing business processes with Amazon Bedrock and Appian’s generative AI skills

This blog post is co-written with Louis Prensky and Philip Kang from Appian.  The digital transformation wave has compelled enterprises to seek innovative solutions to streamline operations, enhance efficiency, and maintain a competitive edge. Recognizing the growing complexity of business processes and the increasing demand for automation, the integration of generative AI skills into environments …

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Governing the ML lifecycle at scale, Part 4: Scaling MLOps with security and governance controls

Governing the ML lifecycle at scale, Part 4: Scaling MLOps with security and governance controls

Data science teams often face challenges when transitioning models from the development environment to production. These include difficulties integrating data science team’s models into the IT team’s production environment, the need to retrofit data science code to meet enterprise security and governance standards, gaining access to production grade data, and maintaining repeatability and reproducibility in …

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