Category: Artificial Intelligence

This blog post shows how Infor uses generative AI services on Amazon Web Services (AWS) to help customers speed up productivity and solve industry-specific challenges

In today’s fast-paced digital landscape, the integration of AI in DevOps is changing how organizations balance innovation with compliance requirements. Generative AI tools have enhanced developer productivity, with estimates suggesting up to 45% improvement in efficiency, while creating new challenges for quality control and regulatory compliance. Through solutions like SpiraTeam from Inflectra, organizations can now leverage AI to modernize their quality and compliance processes while maintaining rigorous safety standards, particularly crucial for regulated industries like healthcare, finance, and utilities.

As customer expectations evolve and data volumes grow exponentially, organizations face unprecedented challenges in managing and activating customer data effectively. Snowplow, a behavioral data collection platform, combined with Databricks Lakehouse platform, creates a scalable foundation for building a next-generation composable CDP on AWS. This solution enables organizations to collect, process, and activate customer data at scale while maintaining complete data ownership and control.

In the rapidly evolving landscape of Generative AI (GenAI), Orkes Conductor emerges as a powerful orchestration platform that helps organizations manage complex workflows, integrate with AWS services, and implement essential safeguards for GenAI applications. The platform offers pre-built LLM tasks, robust error handling, and monitoring capabilities, enabling developers to create sophisticated AI workflows while providing enterprise features like RBAC, audit logs, and versioning for supported applications.

Learn how an AWS Advanced Technology Partner, Langfuse, offers an open-source LLM engineering platform that helps developers monitor, debug, analyze, and iterate on their LLM applications. Langfuse LLM engineering platform helps enterprises gain visibility into their LLM applications while seamlessly integrating with Amazon Bedrock and other popular AI frameworks.

By Paramdeep Singh, Co-Founder – Shorthills AI, By Ganesh Sawhney, Sr Partner Solutions Architect – AWS, By Henry Issac Mudumala, APJ Lead Strategic Partnerships – Datastax DataStax Introduction Extracting value from unstructured data remains a challenge for organizations. They struggle to extract value from emails, reports, legal documents, and other digital assets, which delays decision-making. […]

Adobe Experience Platform, AWS, and Merkle’s Bring Your Own Model (BYOM) accelerator are transforming customer experience personalization at scale. This integration combines AEP’s data foundation, AWS’s enterprise AI capabilities, and Merkle’s ML model integration to deliver highly targeted customer experiences. The solution enables organizations to reduce implementation costs by 60% while leveraging custom ML models and generative AI for enhanced customer engagement

AWS and Intel are collaborating to make Large Language Models (LLMs) more accessible and cost-effective for enterprises by running Small Language Models (SLMs) directly on CPUs. By offering distilled versions of models like DeepSeek-R1, they enable efficient, cost-effective deployments that maintain high performance while running on standard hardware.

In this post, we explain how Dynatrace provides end-to-end monitoring and visibility into generative AI applications utilizing Amazon Bedrock models allowing for comprehensive LLM observability.

GoML, an AWS Advanced Consulting Partner, collaborated with a leading Asian EdTech organization to revolutionize exam preparation through AI. Their Amazon Bedrock-powered solution helps students prepare for competitive exams like JEE Advanced, NEET, and Gaokao. The platform achieves 95% accuracy in solving complex questions while reducing student preparation time by 80%, delivering precise, step-by-step solutions that enhance learning outcomes.