Foundation uses data generated during Phantom robot deployments to retrain its proprietary AI action models, according to CEO Sankaet Pathak in a March 2025 interview. When a human operator remotely intervenes to correct a robot's behavior, that intervention is labeled and fed back into the model. Sacra reports that this feedback loop is built into Foundation's business model, with larger fleets producing more training data and improving model accuracy over time.

According to Sacra, Foundation's business model is structured so that each robot deployment generates training data that feeds back into its proprietary AI models. When a human operator intervenes via teleoperation to correct a robot's behavior, that intervention is labeled and used as training data to improve the model, as described by CEO Sankaet Pathak in a March 2025 interview. This approach means that AI model performance is directly tied to the scale of the robot fleet; a larger deployed fleet produces more diverse operational data, enabling more robust model generalization over time.