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Case Study: Government & Public Sector 

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Cleaning Up AI Governance in the Public Sector

A government agency adopted AI to streamline public service applications and policy analysis. Instead of efficiency, they got mass confusion—outdated data models, biased decision-making, and public trust eroding as errors piled up. Regulators weren’t happy, and neither were citizens.

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The Problem

- Built an AI governance framework to ensure transparency and accountability.
- Standardized data sources to eliminate outdated, biased, or conflicting inputs.
- Implemented policy analysis tools that explained why decisions were made.

What We Did

✔ AI-driven policy recommendations backed by actual reliable data.
✔ Bias in service eligibility decisions reduced by 35%.
✔ Increased public trust by ensuring transparency in AI decision-making.

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Results

Government AI can’t afford to be a black box. If citizens and regulators don’t trust the system, it doesn’t work. We made sure this agency’s AI was accountable, explainable, and legally defensible—before it became a headline.

The Takeaway

Danny Katz Consulting

We help companies fix knowledge chaos, streamline AI governance, and build systems that actually work. Whether it’s unsearchable knowledge silos, AI making bad decisions due to bad data, or compliance teams struggling with operational execution—we solve the problems that stall productivity, increase risk, and waste time.