Services (Page 32)

The integration of generative AI capabilities is driving transformative changes across many industries. Although weather information is accessible through multiple channels, businesses that heavily rely on meteorological data require robust and scalable solutions to effectively manage and use these critical insights and reduce manual processes. This solution demonstrates how toContinue Reading

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-scaleContinue Reading

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 distributedContinue Reading

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 usingContinue Reading

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-endContinue Reading

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 ofContinue Reading

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, andContinue Reading