Category: Database

In this post, we explain what IL5 requires, how AWS GovCloud (US) and SAP NS2 meet those requirements together, and how defense organizations can get started.

A distributed approach, one that brings generative AI to the data rather than the reverse, is achievable today using Amazon Web Services (AWS) solutions such as Amazon Bedrock for orchestration, Amazon Neptune for data lineage, and AWS Identity and Access Management (IAM) for source-point security enforcement.

In Part 2 of our two-part series, we discuss the architecture of the Signal-Activated Agent Pattern and its application for proactive government AI. For Part 1, see Signal-activated generative AI: How agencies can reach more people and react faster.

This two-part series introduces the Signal-Activated Agent Pattern—an architectural approach, backed by a deployable Amazon Web Services (AWS) reference implementation, that helps government AI platforms move from generic, reactive question-answering to proactive, contextually personalized decision support. With this solution, agencies can reach more people, respond faster, and deliver the right value to the right official at each decision point.

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

This post introduces the Geospatial Power Pack, a Kiro power package that turns Kiro into a unified, AI-assisted geospatial workspace. Kiro is an agentic development environment created by Amazon Web Services (AWS). It helps developers and teams turn prompts into executable specs, validate code correctness to find bugs that unit tests miss, and build across large codebases with parallel agents that learn from every session.

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.

Credit unions exist to serve members, not to run data centers. Every hour our team spends on infrastructure is an hour not spent on the question a member actually cares about: “Is my money safe, is my experience easy, and is my credit union on my side?” Moving to a serverless, managed-service foundation on Amazon Web Services (AWS) means our engineers spend their time on membership modeling, fraud analytics, and AI augmentation instead of capacity planning.

This post is for two audiences. The first is agencies already running MARS-E-compliant workloads on AWS that are looking to map their existing posture onto the new framework. The second is agencies planning a migration from on-premises infrastructure where ARC-AMPE will be in scope from the first day.