Composable Models

Topic

Composable models are modular, reusable components in machine learning, artificial intelligence, and data engineering that can be dynamically combined to solve complex tasks. In AI, this approach allows independent neural networks or diffusion models to be composed during inference to generate complex outputs without retraining. In data modeling and semantic layers, composable models treat metrics and dimensions as modular building blocks to eliminate semantic drift and scale consistent business logic.