AWS Public Sector Blog
Author: Nikhil Nayar
Nikhil is a solutions architect at Amazon Web Services (AWS). He focuses on helping the US federal government accelerate its journey to the cloud. Before joining AWS, Nikhil spent 16 years in the field of application architecture and development, working with enterprise customers and service providers. He lives in Virginia with his wife and child.
How federal agencies can optimize document processing using advanced AI with human oversight
Federal agencies typically collect, manage, use, and distribute a wide array of documents. Storing and distributing federal agency documents is often a complicated process; documents can range from structured formats to free-flowing documentation with personal identifiable information (PII) that needs careful redaction. And because federal agencies cover a wide breadth of domains, it is challenging to develop a one-size-fits-all approach for document processing. In this post, we explore an example of how a federal agency can use Amazon Web Services (AWS) to design and deploy a solution that addresses this document processing challenge.
Improve road safety by analyzing traffic patterns with no-code ML using Amazon SageMaker Canvas
To improve safety and convenience, transportation agencies amass a substantial volume of data. However, these organizations encounter challenges in data accuracy validation due to issues related to data quality and occasional missing information. With the incorporation of new artificial intelligence and machine learning capabilities from Amazon Web Services (AWS), they can take advantage of no-code solutions to identify and address data gaps.