Category: Generative AI

This post explains how Shorthills AI’s collaboration with AWS and DataStax’s Astra DB employs advanced search technologies and natural language processing for enterprise search. This collaboration supports customers making data driven business decisions by leveraging AWS’s enterprise-grade security features alongside DataStax’s high-performance vector search capabilities.

The growing demand for generative AI (GenAI) applications has led to a corresponding demand for compute resources that can run these workloads efficiently. In this post we share a step-by-step guide for optimizing GenAI inference workloads using AWS Graviton-based instances. We walk you through downloading Arcee AI SLMs, applying quantization techniques, and deploying models for efficient inference on AWS Graviton instances.

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.

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.

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.

Discover how Capgemini and AWS collaborated to create TELme, a groundbreaking generative AI solution that revolutionizes product research and design in manufacturing. By enabling engineers to efficiently search and summarize vast repositories of technical content using natural language queries, TELme significantly reduces design lifecycle timelines and accelerates time-to-market for new products.

Metal Toad, an AWS Advanced Consulting Partner, demonstrates how to effectively leverage Generative AI and Machine Learning for business solutions. Through case studies with AlertWest and GeniusVets, they showcase the power of AWS services like Amazon Bedrock and SageMaker in creating innovative AI applications, highlighting the importance of choosing the right AI approach for specific business needs.

Valmiki, developed by Genese Solution, is an AI-powered document generation platform. It automates workflows, minimizes errors, and ensures compliance, empowering businesses to stay competitive in today’s fast-paced market. The platform offers customizable templates, a simple interface, and scalable infrastructure to streamline document creation across departments.