Last updated: April 23, 2026
SeaOtter currently has three relevant data surfaces: the web benchmark and pilot intake, the desktop MVP's device-local observer, and opt-in shadow observation for pilot or research workflows.
SeaOtter's baseline model training today is primarily based on synthetic or non-user data. Observed workflow data is not taken from general desktop use by default. In the current implementation, only opt-in shadow observation with an explicit usage scope can materialize into the observed-workflow research queue, and only the training-corpus scope is marked training-eligible. Reviewed samples outside their retention window, or missing audit/provenance controls, are blocked from training planning.
Desktop MVP data is currently stored locally by the app on your device. Shadow observation and benchmark data are stored in SeaOtter systems when those flows are used. For tenant-authenticated observed-data flows, SeaOtter has a retention enforcement control that can delete expired shadow windows, linked shadow benchmark runs, and observed workflow samples. Fully automated retention coverage across every MVP surface is still being implemented. We do not sell personal data.
Current controls depend on the surface:
SeaOtter does not yet provide a single self-serve endpoint that exports or deletes every record across benchmark, pilot, shadow, and research systems.
Email privacy@seaotter.ai for any data requests.
Questions about privacy? Email privacy@seaotter.ai