How Zytheris handles models, prompts, and evidence.
There is no weight-upload form. Shelf packs are trained in our lab on public checkpoints. For a custom pack we pull a checkpoint we are granted (public ID, gated repo, or private access), on GPUs we provision for that model’s size, then import features plus evidence into your workspace. Checkpoint files never pass through the website.
Feature dictionaries are trained offline, not in the browser. Activation dumps are not uploaded through the web UI.
Account API keys can call pack, steer, and report endpoints for your team. Steer jobs run on private GPU workers. There is no public, unauthenticated inference endpoint.
Security questions: hello@zytheris.ca.