Model aggregation gives users one place to discover, compare, select, or invoke models from different developers. A product may add common prompting, media tools, billing, storage, templates, and routing while relying on underlying providers for inference.
Aggregation can create value through convenience and workflow design without training frontier models. The platform still needs accurate model identity, transparent pricing, compatibility checks, privacy controls, and clear responsibility when provider behavior changes.
ELI5
Model aggregation puts access to several AI models inside one product. Users can choose or switch models without setting up a separate application for every model provider.
For example, a creative platform may offer several image and video models behind one interface with shared project storage and prompt tools. It should clearly show which model runs each request and how the provider handles data and cost.
