OptimalCAT is a production-grade Computer Adaptive Testing (CAT) engine designed for both psychometricians running simulations and IT engineers deploying to production.
It builds on the shadow-test approach and leverages state-of-the-art Mathematical Programming solvers to deliver tailored, optimal tests to every student. It ensures that test blueprints and constraints are always met, and measurement accuracy is maximized.
The engine is built as a microservice with a REST API interface. It can integrate seamlessly into test delivery systems.

We believe every student deserves the most accurate measurement.
Latest Version: OptimalCAT-2.5-windows.zip (Manual)
Core Team: Jie Li, PhD
Wim J. van der Linden, PhD
Richard J. Patz, PhD
Support: OptimalCAT@outlook.com
