Tag: Thought Leadership

Discover how hybrid elasticity introduces a zero-migration data access model that decouples data residency from compute elasticity, enabling enterprises to transform existing data centers into dynamic hybrid data hubs with on-demand cloud scale without moving data.

Most AI systems today have no direct understanding of the physical world because the underlying spatial data requires purpose-built preprocessing before AI can use it. By using Wherobots, built on AWS, you can transform petabyte-scale spatial data in Amazon S3 into context that AI can reason about through distributed inference, a spatial query engine, and agentic AI integrations. Learn how customers like Leaf Agriculture, SatSure, and Aarden use Wherobots on AWS to operationalize earth observation data, accelerate spatial processing by up to 300 times, and build AI systems grounded in physical reality.

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.

Amazon CloudWatch Logs centralization offers AWS partners and customers a streamlined alternative to complex, per-account log aggregation pipelines — consolidating logs from across multiple AWS accounts and regions into a single ingestion point for Splunk. By integrating natively with AWS Organizations, the solution automatically onboards new accounts and log groups, reducing operational overhead and total cost of ownership while preserving security boundaries and full data lineage.

The race to deploy AI agents is accelerating — and the organizations pulling ahead are those that build trust from day one. In this joint blog, PwC Australia and AWS deliver a practical blueprint for deploying AI agents safely at scale, answering the three critical questions your board will ask. Governance, observability, and auditability aren’t constraints on speed — they’re your competitive advantage.

SAS Viya Workbench on AWS provides a unified cloud environment for Python, R, and SAS, letting teams focus on building models instead of managing infrastructure. Its split-plane architecture keeps your data securely within your AWS account while SAS handles orchestration. With elastic scalability, pre-configured environments, and built-in collaboration, teams can accelerate analytics innovation from day one.

Modern software teams no longer need to choose between deployment speed and security. CircleCI’s implementation of the AWS Deployment Pipeline Reference Architecture demonstrates how to build enterprise-grade deployment pipelines that deliver 50% faster deployments while reducing security vulnerabilities by 85%. This reference implementation combines the robust cloud infrastructure of AWS with the flexible CI/CD platform of CircleCI, providing a ready-to-fork blueprint that organizations can customize and deploy in an afternoon.

Legacy application migrations can slow innovation and drain resources. Impetus LeapLogic simplifies modernization by automating code, pipeline, and validation workflows—accelerating migration to Amazon SageMaker with unmatched speed and confidence. Discover how LeapLogic and SageMaker empower enterprises to transform legacy workloads on AWS with reduced risk, greater efficiency, and faster business results.