The United States (U.S.) government publishes millions of pages of reports annually—a cornerstone of democratic accountability and transparency. Yet despite being publicly available, much federal reporting data is not readily usable for modern analysis, including AI-driven research. Reports are often difficult to access in bulk, hard to analyze consistently, and…

At the Program Integrity Alliance (PIA), our mission is to strengthen integrity in government through data, evidence, and collaboration. To advance that mission, we’ve developed tools like Recommendation Spotlight and GovQuery, which make complex public data easier to explore, analyze, and apply to real-world decision-making.  With the launch of PIA…

Why GovQuery Government produces vast amounts of information, but much of it is scattered and hard to search. GovQuery, our custom search engine, brings together key sources in one place to make this knowledge easier to find and use. Coupled with AI capabilities, GovQuery becomes a platform for synthesizing resources…

Making use of AI isn’t just about leveraging chatbots. One of the most profound impacts today is in software development. In the past 6 months, AI-assisted coding has advanced rapidly, helping organizations to build more software with fewer resources. For new nonprofits like the Program Integrity Alliance (PIA), this evolution

The federal government is stepping up efforts to expand the use of Treasury’s Do Not Pay database as a tool to prevent fraud and improper payments. In this article by Justin Double of the Federal News Network, Linda Miller, president of the Program Integrity Alliance, said the move addresses

Custom AI Can Age Fast  With a great deal of Fear of Missing Out (FOMO), thousands of organizations around the world committed to developing custom in-house solutions using Generative AI (Gen AI).    Soooo many chatbots. 🙂  It’s understandable, the power of Large Language Models (LLMs) to interpret unstructured data…

PIA and the Association of Certified Fraud Examiners (ACFE) hosted a roundtable at the ACFE’s Annual Global Fraud Conference in Nashville, Tennessee. This roundtable included conference participants from industry, government, and academia to share insights and practices for measuring value-for-money (V4M) and return on investment of fraud prevention efforts.

Data can fight fraud, but only if we break down silos without breaking trust. This paper explores how the federal government can expand data sharing to prevent fraud while upholding privacy, outlining a path to smarter, safer governance. Find the paper here.

The U.S. loses hundreds of billions annually to fraud in public programs, yet anti-fraud policy still relies heavily on “pay and chase” enforcement and recovery. A Value-for-Money (V4M) approach offers a better standard for evaluating anti-fraud efforts by highlighting the impact and cost-effectiveness of both recovery dollars and prevention.

We held a demo of our data work and AI tools in Washington, D.C. for a group of stakeholders working in government, nonprofits, Congress, and industry.  Through our AI tools, we want to make it easier for people working on program integrity and antifraud issues to assess the landscape