Harmonization is not a one-time event. Source systems change, coding practices drift, and new sites join. The Data Harmonization Model treats harmonization as a continuous process across sites, detecting where the harmonized model has drifted from its sources and repairing it, drawing on the lab's published work on self-healing systems.
This is a technical report on internal research. The model runs in production inside the platform underneath Axiomera and Conduit.
Related published work: A quantum-inspired, biomimetic and fractal framework for self-healing AI code generation.