Category: Customer Solutions

When implementing machine learning workflows in Amazon SageMaker Canvas, organizations might need to consider external dependencies required for their specific use cases. Although SageMaker Canvas provides powerful no-code and low-code capabilities for rapid experimentation, some projects might require specialized dependencies and libraries that aren’t included by default in SageMaker Canvas. This post provides an example of how to incorporate code that relies on external dependencies into your SageMaker Canvas workflows.

Discover how to build a GenAI powered virtual IT troubleshooting assistant using Amazon Q Business. This innovative solution integrates with popular ITSM tools like ServiceNow, Atlassian Jira, and Confluence to streamline information retrieval and enhance collaboration across your organization. By harnessing the power of generative AI, this assistant can significantly boost operational efficiency and provide 24/7 support tailored to individual needs. Learn how to set up, configure, and leverage this solution to transform your enterprise information management.

This post presents a comprehensive AIOps solution that combines various AWS services such as Amazon Bedrock, AWS Lambda, and Amazon CloudWatch to create an AI assistant for effective incident management. This solution also uses Amazon Bedrock Knowledge Bases and Amazon Bedrock Agents. The solution uses the power of Amazon Bedrock to enable the deployment of intelligent agents capable of monitoring IT systems, analyzing logs and metrics, and invoking automated remediation processes.

In this post, we explore why Asure used the Amazon Web Services (AWS) post-call analytics (PCA) pipeline that generated insights across call centers at scale with the advanced capabilities of generative AI-powered services such as Amazon Bedrock and Amazon Q in QuickSight. Asure chose this approach because it provided in-depth consumer analytics, categorized call transcripts around common themes, and empowered contact center leaders to use natural language to answer queries. This ultimately allowed Asure to provide its customers with improvements in product and customer experiences.

This post provides an overview of a custom solution developed for GoDaddy, a domain registrar, registry, web hosting, and ecommerce company that seeks to make entrepreneurship more accessible by using generative AI to provide personalized business insights to over 21 million customers. In this collaboration, the Generative AI Innovation Center team created an accurate and cost-efficient generative AI–based solution using batch inference in Amazon Bedrock, helping GoDaddy improve their existing product categorization system.

In this post, we dive deeper into one of MaestroQA’s key features—conversation analytics, which helps support teams uncover customer concerns, address points of friction, adapt support workflows, and identify areas for coaching through the use of Amazon Bedrock. We discuss the unique challenges MaestroQA overcame and how they use AWS to build new features, drive customer insights, and improve operational inefficiencies.

In this post, we demonstrate how Octus migrated its flagship product, CreditAI, to Amazon Bedrock, transforming how investment professionals access and analyze credit intelligence. We walk through the journey Octus took from managing multiple cloud providers and costly GPU instances to implementing a streamlined, cost-effective solution using AWS services including Amazon Bedrock, AWS Fargate, and Amazon OpenSearch Service.

This post is co-authored with Sundeep Sardana, Malolan Raman, Joseph Lam, Maitri Shah and Vaibhav Singh from Verisk. Verisk (Nasdaq: VRSK) is a leading strategic data analytics and technology partner to the global insurance industry, empowering clients to strengthen operating efficiency, improve underwriting and claims outcomes, combat fraud, and make informed decisions about global risks. […]

In this post, we explain how BMW uses generative AI to speed up the root cause analysis of incidents in complex and distributed systems in the cloud such as BMW’s Connected Vehicle backend serving 23 million vehicles. Read on to learn how the solution, collaboratively pioneered by AWS and BMW, uses Amazon Bedrock Agents and Amazon CloudWatch logs and metrics to find root causes quicker. This post is intended for cloud solution architects and developers interested in speeding up their incident workflows.

Pattern is a leader in ecommerce acceleration, helping brands navigate the complexities of selling on marketplaces and achieve profitable growth through a combination of proprietary technology and on-demand expertise. In this post, we share how Pattern uses AWS services to process trillions of data points to deliver actionable insights, optimizing product listings across multiple services.