Tag: Generative AI

When AI infrastructure costs consumed 40% of per-interview revenue, InterWiz knew their single-provider architecture couldn’t support profitable growth. By partnering with AWS Advanced Tier Services Partner Emumba to migrate from Azure OpenAI to Amazon Bedrock, InterWiz reduced AI costs by 90%, improved response times by 55%, and maintained 99.9% uptime, all with zero service disruption. Learn how a multi-model architecture on Amazon Bedrock transformed InterWiz’s cost-to-revenue ratio and created lasting competitive advantage.

The AI-Driven App Modernization Platform from Pega and AWS enables enterprises to incrementally transform legacy applications from mainframes to monolithic applications into intelligent, cloud-native workflows using AI-powered discovery, low-code design, and the strangler fig pattern, cutting modernization timelines from years to months without disrupting critical business operations.

DevRev built real-time AI guardrails into its enterprise agent system, powered by Amazon Nova 2 Lite through Amazon Bedrock. The guardrail layer evaluates every user input against default and custom policies in 247ms average latency without degrading the conversational experience. This post explores how DevRev delivers high support ticket automation and cost reduction while keeping content on-policy and safety controls firm.

Learn how DXC Technology used Amazon Q Developer to help its customer modernize over 80 microservices and multiple micro-frontend applications, upgrading from older Angular and .NET versions while achieving a 60–75% reduction in overall upgrade effort. By combining structured prompt engineering with AI-driven automation, DXC transformed a high-risk, months-long modernization initiative into a fast, secure, and scalable success, saving an estimated 1,200 to 1,400 developer hours while strengthening security and compliance across the platform.

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.

Learn how the integration of Amazon Nova multimodal intelligence with Bria Fibo’s deterministic visual foundation model solves the enterprise challenges of unpredictable outputs, inconsistent branding, and legal uncertainty in AI image generation. This post explores how structured Visual Generation Language (VGL) and 100% licensed training data deliver reproducible, brand-consistent visuals at scale—transforming generative AI from an experimental technology into a production-ready content pipeline available in AWS Marketplace and Amazon SageMaker AI.

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.