Tag: Artificial Intelligence

AWS has launched the Partner-Led Forward Deployed Engineering (FDE) motion, extending its $1 billion investment in agentic AI deployment to strategic consulting partners. This new capability builds dedicated, AWS-credentialed engineering teams within leading partners to deliver production agentic systems in days, not months, using a reusable delivery harness that compounds expertise with every engagement, ensuring customers achieve real outcomes on real data under real governance.

As AI workloads scale on AWS, the API layer becomes the primary security surface where every prompt, model response, and agent action flows through. AWS foundational controls and Wallarm runtime API security work together to deliver continuous discovery, behavioral threat detection, and output validation, helping organizations secure agentic systems without re-architecting their environments.

As cloud-native environments expand, security and operations leaders face mounting pressure to reduce response times while managing growing alert volumes and team capacity. Elastic’s AI-powered features on Amazon Bedrock automate the path from detection to resolution across both security and observability workflows. Learn how conversational agents, automated workflows, and custom AI agents accelerate incident response and root cause analysis on AWS.

As AI agents take actions across systems on behalf of your users, identity and access management must sit at the center of your security strategy. In this post, we show how Auth0 for AI Agents and Amazon Bedrock AgentCore work together to authenticate users, secure agent-to-agent communication, govern tool access, and enforce fine-grained authorization. Learn how to extend your existing identity infrastructure to agentic workloads and replace fragmented security with a consistent, maintainable model.

Open-weight large language models are being released by research institutions worldwide, but turning published weights into production inference services remains a challenge—especially under strict data residency requirements. This post shows how Public AI built a scalable inference platform on Amazon EKS and Intel-powered Amazon EC2 instances to serve Switzerland’s Apertus model family, and why this architecture provides a repeatable blueprint for sovereign LLM initiatives.

Accenture and AWS are closing the data readiness gap that stalls most enterprise AI initiatives with three new agentic AI solutions—now available in AWS Marketplace—that autonomously discover, migrate, govern, and make enterprise data consumable for generative AI and agentic applications. Built on Amazon Bedrock AgentCore and backed by 16 years of partnership experience, these solutions help organizations turn fragmented, legacy data estates into strategic assets ready for agentic AI at enterprise scale.

What if one database could handle transactions, analytics, and semantic vector search for your AI agents—all without managing separate systems? TiDB Cloud on AWS, integrated with Amazon Bedrock, delivers a unified, serverless architecture purpose-built for the demands of autonomous AI. In this post, PingCAP and AWS walk you through the reference architecture, real-world use cases, and the key design decisions to make your generative AI applications production ready using the TiDB console.

Integration complexity—not technology—remains the biggest barrier to deploying AI in supply chain operations, with custom API development consuming up to six months of engineering effort per project. Genpact’s Kinaxis MCP Server, built on Amazon Bedrock AgentCore, collapses that timeline from 12 weeks to just 3 days by replacing dozens of custom integrations with a single, secure interface powered by the Model Context Protocol standard. Learn how organizations running Kinaxis RapidResponse on AWS are achieving up to 18% improvement in forecast accuracy and 23% reduction in stockout rates—with enterprise-grade security and session isolation built in from day one.

Real-time AI agents are transforming how businesses make decisions—but only when they can access analytical data at conversational speed. This post shows you how to integrate ClickHouse Cloud with Amazon Quick using Model Context Protocol (MCP), delivering sub-second query responses across billions of data points. Learn how to empower your teams with natural language access to live operational data, enabling instant insights and actions without writing a single line of SQL.

Inflectra, an AWS ISV Accelerate Partner, has developed Rapise—an AI-powered test automation platform that leverages Amazon Bedrock and Amazon Nova to address the testing bottleneck created by modern agentic coding tools. By automatically generating test scripts, adapting to application changes with self-healing capabilities, and providing intelligent defect detection, Rapise reduces QA cycle times by up to 70% while delivering audit-ready compliance tracking for regulated industries including healthcare, life sciences, and financial services.