Category: Customer Solutions

Delivering successful COBOL modernization requires a solution that can reverse engineer deterministically, produce validated and traceable specs, and help those specs flow into any AI-powered coding assistant for the forward engineering. A successful modernization requires both reverse engineering and forward engineering. Learn more about COBOL in this post.

This post explores the implementation of Dottxt’s Outlines framework as a practical approach to implementing structured outputs using AWS Marketplace in Amazon SageMaker.

In this post, we explore how Sonrai, a life sciences AI company, partnered with AWS to build a robust MLOps framework using Amazon SageMaker AI that addresses these challenges while maintaining the traceability and reproducibility required in regulated environments.

In this post, we explain how you can use the Flyte Python SDK to orchestrate and scale AI/ML workflows. We explore how the Union.ai 2.0 system enables deployment of Flyte on Amazon Elastic Kubernetes Service (Amazon EKS), integrating seamlessly with AWS services like Amazon Simple Storage Service (Amazon S3), Amazon Aurora, AWS Identity and Access Management (IAM), and Amazon CloudWatch. We explore the solution through an AI workflow example, using the new Amazon S3 Vectors service.

This post shows you how to implement intelligent notification filtering using Amazon Bedrock and its gen-AI capabilities. You’ll learn model selection strategies, cost optimization techniques, and architectural patterns for deploying gen-AI at IoT scale, based on Swann Communications deployment across millions of devices.

LinqAlpha is a Boston-based multi-agent AI system built specifically for institutional investors. The system supports and streamlines agentic workflows across company screening, primer generation, stock price catalyst mapping, and now, pressure-testing investment ideas through a new AI agent called Devil’s Advocate. In this post, we share how LinqAlpha uses Amazon Bedrock to build and scale Devil’s Advocate.

In this post, we discuss how Amazon Nova in Amazon Bedrock can be used to implement an AI-powered image recognition solution that automates the detection and validation of module components, significantly reducing manual verification efforts and improving accuracy.

Iberdrola, one of the world’s largest utility companies, has embraced cutting-edge AI technology to revolutionize its IT operations in ServiceNow. Through its partnership with AWS, Iberdrola implemented different agentic architectures using Amazon Bedrock AgentCore, targeting three key areas: optimizing change request validation in the draft phase, enriching incident management with contextual intelligence, and simplifying change model selection using conversational AI. These innovations reduce bottlenecks, help teams accelerate ticket resolution, and deliver consistent and high-quality data handling throughout the organization.

Working with the Generative AI Innovation Center, New Relic NOVA (New Relic Omnipresence Virtual Assistant) evolved from a knowledge assistant into a comprehensive productivity engine. We explore the technical architecture, development journey, and key lessons learned in building an enterprise-grade AI solution that delivers measurable productivity gains at scale.

Associa collaborated with the AWS Generative AI Innovation Center to build a generative AI-powered document classification system aligning with Associa’s long-term vision of using generative AI to achieve operational efficiencies in document management. The solution automatically categorizes incoming documents with high accuracy, processes documents efficiently, and provides substantial cost savings while maintaining operational excellence. The document classification system, developed using the Generative AI Intelligent Document Processing (GenAI IDP) Accelerator, is designed to integrate seamlessly into existing workflows. It revolutionizes how employees interact with document management systems by reducing the time spent on manual classification tasks.