Category: Amazon Machine Learning

to meet this demand.
The Kayode Alabi Leadership and Career Initiative (KLCI Africa), a nonprofit social enterprise headquartered in Lagos, Nigeria, set out to solve this problem using generative AI and Amazon Web Services (AWS). In this post, we describe how KLCI Africa built Rafiki AI, a WhatsApp-based generative AI career advisor that delivers personalized career guidance to underserved and displaced youth in under 2 minutes.

This post explores how an agentic AI architecture on Amazon Web Services (AWS) modernizes the procurement lifecycle from solicitation to proposal evaluation while maintaining compliance with government regulations including United States of America FAR (Federal Acquisition Regulation),United States of America DFARS (Defense Federal Acquisition Regulation), and Canadian procurement frameworks (Public Service Procurement Canada (PSPC) /Shared Services Canada (SSC).

In this post, we walk through three extended capabilities of Amazon S3: Amazon S3 Metadata, Amazon S3 Vectors, and Amazon S3 Tables and explore how each maps to real challenges government agencies face today.

This post presents two complementary patterns for implementing per-user token guardrails on Amazon Bedrock from Amazon Web Services (AWS).

This post is a follow-up to our March 2025 blog post, UTHealth Houston’s iDFax transforms medical fax management with Amazon Bedrock, which introduced the iDFax pilot and its early results.

Every major agent framework has a security model for this. Amazon Web Services (AWS), Microsoft, and Google each ship agent solutions with authentication and credential management built in. Amazon Bedrock Agents, for example, enforces AWS Identity and Access Management (IAM)-based authorization on which AWS Lambda functions, Amazon Simple Storage Service (Amazon S3) buckets, and Amazon Bedrock Knowledge Bases an agent might invoke.

This post shows how public sector and enterprise teams can build an agentic AI-powered classification system on Amazon Web Services (AWS) using the Strands Agents SDK, Amazon Bedrock, and serverless services. You will learn the architecture, the agent workflow, and how to implement this system using the Strands Agents SDK.

Learn how Amazon Web Services (AWS) offers a fundamentally different approach. By deploying agentic AI—specialized AI agents that work collaboratively to analyze, validate, and route documentation—federal agencies can dramatically accelerate conformity processing while maintaining or improving quality and compliance standards.

The Translational AI Center (TrAC) at Iowa State University is a pre-competitive research hub that bridges the gap between academic AI breakthroughs and real-world deployment. With over 70 affiliated faculty spanning seven ISU colleges, TrAC breaks down disciplinary silos and organizes research across thematic areas, including food and energy systems, healthcare, autonomy, materials design, and AI ethics.

The United States General Services Administration (GSA) Pegasys Financial Management program plays a vital role in managing the agency’s financial operations, processing hundreds of billions of dollars in transactions annually for GSA and 40 partner agencies, boards, and commissions. When GSA needed to modernize the infrastructure supporting this mission-critical system, the agency faced a significant challenge. It needed to migrate 30 terabytes of production data, over 100 virtual machines, and 70 external system interfaces to the cloud—all within 6 months while maintaining uninterrupted availability.