Public sector clients face fiscal inflection: aging workforces, tightening budgets, and rising citizen expectations. Galatine Technologies bridges the gap between legacy systems and proactive, AI-driven governance.
A state-level revenue authority approached Galatine Technologies struggling with a tax gap exceeding hundreds of millions of dollars annually. Reactive fraud detection methods analyzed returns months after submission, allowing intentional evasion to compound. Internally, fragmented data across tax administration, public safety, and infrastructure departments meant every team operated from a different version of the truth.
Compounding the issue, agency leaders faced the same constraints driving the entire public sector: aging workforces, repetitive administrative burdens, and capital tied up in legacy infrastructure that demanded reactive (rather than predictive) maintenance.
A phased engagement that combines AI strategy, data engineering, and operational consulting to move your organization from reactive to predictive.
We built API layers over existing legacy back-ends, allowing modern AI services to interface with mainframe data without disruption. A unified context library replaced siloed departmental data.
Automated data pipelines ingested fiscal records, financial filings, and offshore disclosures into a central warehouse. Tree-based ensemble models (Random Forest + XGBoost) with attention-mechanism DNN layers identified suspicious patterns in real time.
IoT sensors, structural health monitoring, and digital twin models replaced reactive bridge and road inspections. Computer vision pipelines automated defect detection across the asset portfolio.
Generative AI assistants automated HR resume screening, internal HR inquiry resolution, and 911 non-emergency call diversion. Predictive attrition models flagged retention risk among critical STEM staff.
The performance gains our clients realize when they replace fragmented operations with intelligent, data-engineered systems.
For a state revenue authority, our AATO framework delivered a hybrid AI model achieving 91% precision and 88% recall on fraud detection. Combined with our infrastructure modernization work, the engagement produced $380 million in taxpayer savings and recovered $3.1 million in quantified analytics savings within 24 months by centralizing data from 14 disconnected departmental systems.
Whether you're modernizing tax oversight, infrastructure maintenance, or citizen services, our team is ready to design an AI roadmap aligned to your mandate.
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