Keras Core provided a unified interface for deep learning model development across multiple backends. It enabled users to write Keras code that could execute on TensorFlow, JAX, or PyTorch computation frameworks without code changes. This multi-backend approach allowed developers to leverage the strengths of different frameworks while maintaining a consistent API.