Differing federal requirements for public benefit applications create significant barriers for applicants and complicate state efforts to integrate services.
A case study documenting how a human-centered claimant portal was developed for the New Jersey Department of Labor (NJDOL) to modernize unemployment insurance access using agile development and API technology.
Building modular, open-source, human-centered software is necessary to create equitable government services fit for the digital age. Nava emphasizes addressing large scale digital service challenges by building and releasing small, modular software components that are loosely-coupled by well-defined APIs. This enables agencies to quickly and conistently deliver services that help people immediately, whilst also building a flexible foundation for long-term technical evolution.
Nava partnered with California's Employment Development Department (EDD) to rapidly develop two cloud-based digital services, enhancing unemployment benefit access during the COVID-19 pandemic.
A case study documenting how a modular API layer was built to support a state-level paid family and medical leave program, improving interoperability, scalability, and user experience.
Usability tests can help teams develop products that are user-centered, accessible, and inclusive. This guide will help you conduct a successful usability test, from coordinating with participants to analyzing your findings.
In 2022, Nava formed its first-ever PAC as part of their initiative to help Montana’s Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) program design a new recertification portal. Leveraging what Nava learned from this experience, this toolkit outlines the necessary steps to form a PAC, including planning a structure for the council, recruiting participants, and other logistics.
The team developed an AI solution to assist benefit navigators with in-the-moment program information, finding that while LLMs are useful for summarizing and interpreting text, they are not ideal for implementing strict formulas like benefit calculations, but can accelerate the eligibility process by leveraging their strengths in general tasks.
Guidance on improving how well AI systems can understand digital content. It emphasizes using machine-readable formats and applying clear content design strategies to enhance both AI processing and human accessibility
