Author: Sanjeev Pulapaka

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.

In this blog post, Sanjeev Pulapaka of AWS explores how agentic AI—deploying multiple specialized agents that understand intent and context—can dramatically accelerate the federal rulemaking lifecycle by addressing its three major bottlenecks: NPRM development, public comment analysis, and final rule clearance.

Government agencies are facing a cybersecurity challenge. Traditional security information and event management (SIEM) systems generate thousands of alerts on a daily basis, overwhelming security operations center (SOC) analysts who spend countless hours manually investigating incidents. Studies show that 70% of alerts turn out to be false positives. This reactive approach creates critical vulnerabilities: alert […]

As state and federal organizations increasingly explore generative AI implementations using Amazon Bedrock, they face a critical challenge: accurately estimating the costs associated with these workloads. In this post, we cover details about estimating costs on Amazon Bedrock.

In this blog post, learn key AWS concepts and services that can help agencies modernize their cloud and data architecture. First, learn two fundamental concepts that agencies need to examine regardless of their technical approach. Then, discover the AWS services that enable agencies to apply these concepts to meet mission needs.

Local public health departments must notify public health agencies, like state health departments or the Centers for Disease Control and Prevention (CDC), of reportable conditions. These departments receive various types of reports of healthcare conditions through email, in addition to more traditional methods such as mail, fax, or phone calls. Local health departments can dramatically reduce the time and costs associated with manually processing email attachments and improve processing efficiency using automation. In this blog post, learn how to create an automated email attachment ingestion, storage, and processing solution powered by artificial intelligence (AI) and machine learning (ML) services from AWS.

Modern applications built using microservices architectures improve customer experience by dramatically reducing the risk of failures in a web application. In this blog post, we present a sample AWS reference architecture of a microservices application built using an architecture framework based in AWS GovCloud (US), which can help support adherence to a Federal Risk and Authorization Management Program (FedRAMP) High Baseline.

Customer experience (CX) has emerged as a key priority in the US following the 2021 Biden Administration Executive Order (EO) to transform federal customer experience and service delivery. Application modernization enables agencies to simplify business processes and provide customers with flexible, interactive, and simple to use applications, resulting in improved CX. In this blog post, we present an AWS architecture framework that agencies can use to develop and deploy a modern application that helps improve CX.

To mitigate synthetic fraud, government agencies should consider complementing their rules-based improper payment detection systems with machine learning (ML) techniques. By using ML on a large number of disparate but related data sources, including social media, agencies can formulate a more comprehensive risk score for each individual or transaction to help investigators identify improper payments efficiently. In this blog post, we provide a foundational reference architecture for an ML-powered improper payment detection solution using AWS ML services.

Government agencies are moving to speed up service delivery, but agencies need to obtain an Authority to Operate (ATO) that demonstrates security compliance prior to implementation, which can take a significant amount of time and can prove to be a challenge in meeting tight deadlines. AWS Partner Booz Allen Hamilton (Booz Allen) uses a platform as a service model on Amazon Web Services (AWS) to enable their customers to rapidly build, test, scan, and deploy their applications — accelerating releases in the federal government from months to days.