CAPSUL-IA proposes a methodology for developing functions common to many industries, based on the design of a set of preconfigured AI solutions tailored to different requirement sets, where a balance is achieved across various relevant metrics.
CAPSUL-IA introduces the concept of AI capsules, understood as containers of AI models adapted to different problems and offering multiple trade-offs between cost, accuracy, inference speed, and robustness—among other metrics.