Category: Thought Leadership

In this post, we explore how Mantle, Amazon’s next-generation inference engine for Amazon Bedrock, implements a zero operator access (ZOA) design that eliminates any technical means for AWS operators to access customer data.

Picture this: Your enterprise has just deployed its first generative AI application. The initial results are promising, but as you plan to scale across departments, critical questions emerge. How will you enforce consistent security, prevent model bias, and maintain control as AI applications multiply?

In this post, we explore three essential strategies for successfully integrating AI into your organization: addressing organizational debt before it compounds, embracing distributed decision-making through the “octopus organization” model, and redefining management roles to align with AI-powered workflows. Organizations must invest in both technology and workforce preparation, focusing on streamlining processes, empowering teams with autonomous decision-making within defined parameters, and evolving each management layer from traditional oversight to mentorship, quality assurance, and strategic vision-setting.

The AWS Customer Success Center of Excellence (CS COE) helps customers get tangible value from their AWS investments. We’ve seen a pattern: customers who build AI strategies that address people, process, and technology together succeed more often. In this post, we share practical considerations that can help close the AI value gap.

In this post, we explore the complete development lifecycle of physical AI—from data collection and model training to edge deployment—and examine how these intelligent systems learn to understand, reason, and interact with the physical world through continuous feedback loops. We illustrate this workflow through Diligent Robotics’ Moxi, a mobile manipulation robot that has completed over 1.2 million deliveries in hospitals, saving nearly 600,000 hours for clinical staff while transforming healthcare logistics and returning valuable time to patient care.

I’m excited to announce AWS Professional Services now offers specialized AI agents including the AWS Professional Services Delivery Agent. This represents a transformation to the consulting experience that embeds intelligent agents throughout the consulting life cycle to deliver better value for customers.

In 2024, we launched the Custom Model Program within the AWS Generative AI Innovation Center to provide comprehensive support throughout every stage of model customization and optimization. Over the past two years, this program has delivered exceptional results by partnering with global enterprises and startups across diverse industries—including legal, financial services, healthcare and life sciences, […]

In this post, we explore the Five V’s Framework—a field-tested methodology that has helped 65% of AWS Generative AI Innovation Center customer projects successfully transition from concept to production, with some launching in just 45 days. The framework provides a structured approach through Value, Visualize, Validate, Verify, and Venture phases, shifting focus from “What can AI do?” to “What do we need AI to do?” while ensuring solutions deliver measurable business outcomes and sustainable operational excellence.

In this post, we explore how Amazon Bedrock AgentCore Memory transforms raw conversational data into persistent, actionable knowledge through sophisticated extraction, consolidation, and retrieval mechanisms that mirror human cognitive processes. The system tackles the complex challenge of building AI agents that don’t just store conversations but extract meaningful insights, merge related information across time, and maintain coherent memory stores that enable truly context-aware interactions.

Learn why customers choose AgentCore to build secure, reliable AI solutions using their choice of frameworks and models for production workloads.