Category: AWS Step Functions

In this post, we explore a human-in-the-loop (HITL) framework in the form of architectural patterns teams can use to introduce agentic AI incrementally into eligibility workflows that are adapted to their programs, policies, and risk tolerances.

A recent State CIO Survey from the National Association of State Chief Information Officers (NASCIO) highlights that modernization extends beyond a single piece of technology. Digital accessibility, AI, modernization funding, cloud, data governance, collaboration, and service delivery are now all connected priorities that influence constituent-facing experiences and the operating models that make those experiences possible. Amazon Web Services (AWS) and partners like Presidio help agencies address these priorities through cloud-based modernization patterns that connect workflow, data, experience, and governance.

In this post, we describe how ITHAKA and Amazon Web Services (AWS) collaborated to build an on-demand PDF accessibility pipeline that remediates documents when users need them, serving researchers while using nonprofit resources responsibly. For organizations managing a large document collection under accessibility compliance deadlines, this post shows there is an affordable, practical path forward that doesn’t require converting an entire library upfront.

In this post, we review how AWS Lambda works today, introduce durable functions, walk through a document processing use case for child welfare, and explain when to choose durable functions over AWS Step Functions.

In this post, we walk through the evidence pipeline, from Amazon Web Services (AWS) Config evaluations and AWS Security Hub findings through transformation and storage, to producing the dual-format output that satisfies FedRAMP 20x Phase 2 completeness requirements.

In this post, we share a reference AWS architecture that healthcare organizations, health plans, and state agencies can use to deploy AI agents while maintaining HIPAA compliance.

In this post, you’ll learn how to build an identity incident review workflow that analyzes an event timeline, converts the findings into a strict incident record, and connects the review to a local account-control lookup. The examples separate observed facts from inferences and keep final incident and remediation decisions with a human reviewer.

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.

Learn how the Boise State University Foundation transformed quarterly Microsoft Excel reports into real-time dashboards using Amazon Quick, a 780-fold improvement that fundamentally changed how leadership makes decisions. It extracts actionable insights from a decades-old legacy system while supporting a major comprehensive fundraising campaign.

In this post, the first in a two-part series, we focus on the detection and forensic readiness side of satellite IR. This post walks through instrumenting your ground segment with Amazon Web Services (AWS) security services and AWS Ground Station so that threats surface before they cause damage, and forensic data is already flowing when an incident occurs.