Category: Generative AI

Explore how Appian’s AI Copilot, powered by Amazon Bedrock is built directly into the Appian platform to assist both business users and developers in common tasks. For business users, AI CoPilot enables conversational data interaction through Records Chat feature, to help find patterns and trends from real-time data, and provides quick access to business specific documents through the Enterprise Copilot. Whereas, for developers, AI Copilot accelerates application development by assisting in requirements gathering to data modeling, UX design and object generation, while also automating test case creation and generating realistic sample data for testing.

While cloud adoption accelerates, many industries still rely on legacy systems for critical workloads. This blog explores how Solace’s PubSub+ facilitates cloud migrations using the Strangler Fig pattern and a data-first approach. PubSub+ enables seamless, real-time data movement across hybrid environments, helping enterprises modernize without disrupting business continuity. Learn how this IDC-recognized event-driven solution addresses key migration challenges.

The blog introduces a five-layer Generative AI Landing Zone architecture on AWS that helps organizations quickly implement and scale AI capabilities while maintaining security and compliance standards. The solution addresses key challenges like compliance delays, pilot-to-production gaps, and limited visibility through features such as automated guardrails, same-day sandboxes, reusable blueprints, built-in observability, and continuous governance.

AWS announces the general availability of AWS Transform for mainframe, a new service that accelerates mainframe modernization using specialized AI agents. This blog showcases how AWS Partners are leveraging the service to streamline customer migrations, reducing transformation timelines from years to months while addressing traditional modernization challenges around speed, complexity, and skills gaps.

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.