Algorithm Registry

To help child welfare agencies prioritize investigations and manage significant volumes of calls by identifying which children are at higher risk.

Compares application details against administrative records to flag benefit applications for additional review.

Ranks incoming non-emergency service requests to help dispatchers assign response priority.

Time-series forecasting model that predicts energy demand to optimize power grid management and reduce costs.

Predicts households at risk of eviction so outreach teams can prioritize legal aid and rental assistance.

Machine learning algorithm that analyzes transaction patterns to identify potentially fraudulent activities in government benefit programs.

A tool designed to prioritize scarce housing resources by predicting an applicant's risk of adverse events (e.g., emergency room visits, mental health stays, or jail bookings) based on administrative data.

Recommendation system that matches job seekers with suitable employment opportunities based on skills, experience, and preferences.

Routes public-service requests to interpreters and multilingual staff based on language needs and urgency.

Recommends library programs and public resources based on community member interests and service needs.

Schedules housing inspections based on complaint history, building age, and prior violation records.

Predictive model that identifies students at risk of dropping out based on attendance, grades, and engagement metrics.

AI-powered system that manages traffic signal timing based on real-time traffic data to reduce congestion and improve commute times.

Classifies transit incident reports to route them to safety, maintenance, or customer support teams.

Flags employers for wage-theft investigation based on complaint patterns and payroll-risk indicators.