mRelief is a nonprofit that helps individuals in all 53 U.S. states and territories determine SNAP eligibility and apply using easy-to-use web and text tools. Their simplified, inclusive approach has supported over 2.7 million people and unlocked over $1 billion in benefits, focusing on minimizing barriers and adapting eligibility rules across states.
The team conducted experiments to determine whether clients would be responsive to proactive support offered by a chatbot, and identify the ideal timing of the intervention.
Benefits Data Trust (BDT) is a nonprofit that connects people to public benefits through a streamlined, phone-based application system called Benefits Launch, which reduces redundant questions and speeds up the process for multiple programs. BDT's approach, supported by a custom-built rules engine, has facilitated over 800,000 benefit enrollments, helping secure over $9 billion for eligible households across seven states.
Github repository for Policy Rules Database, which encodes up-to-date rules and provisions for all major federal and state public assistance programs, taxes, and tax credits.
The Atlanta Fed’s CLIFF tools provide greater transparency to workers about potential public assistance losses when their earnings increase. We find three broad themes in organization-level implementation of the CLIFF tools: identifying the tar- get population of users; integrating the tool into existing operations; and integrating the tool into coaching sessions.
Alluma is a nonprofit that provides digital solutions to simplify eligibility screening and enrollment for social benefit programs, supporting cross-benefit access in 45 counties and two states. Their One-x-Connection product suite streamlines Medicaid and SNAP applications using a business rules engine, with a focus on human-centered design and anonymous, simplified eligibility checks, having helped screen over 10 million individuals and submitted over 67 million applications.
This article explores how legal documents can be treated like software programs, using methods like software testing and mutation analysis to enhance AI-driven statutory analysis, aiding legal decision-making and error detection.
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.
The Digital Identity Community of Practice kick-off event featured key resources, a new research publication on account creation and identity proofing, and insights from multiple speakers.