Platform
The flywheel
Anyone can fine-tune a model once. The difference here is the loop: with consent, real usage trains the next version — and the gains compound.
How it works
A Flywheel model ships trained, useful, and versioned. When you opt in, the business-side turnsfrom your usage — de-identified — become training signal for the next version of that niche’s model. We ship a new version only when it measurably beats the last, so quality moves in one direction. De-identification is defense-in-depth, not the lawful basis: consent is.
Consent & control
Contribution is opt-in and reversible. By default nothing is collected for training. When you turn it on, an append-only consent event is recorded and ingestion is gated on it in real time. Flip ghost mode any time and the pipe goes dark immediately — new usage stops flowing. Self-hosting is unaffected: running the open weights sends nothing, regardless of this setting.
Private vs shared models
By default, your consented usage trains a model that is yours alone — never pooled with anyone else. A shared, niche-wide model only turns on once enough businesses contribute that no single one is identifiable, and only with separate, explicit consent. For liability-bearing or privileged verticals, a private single-tenant model under a DPA keeps your data fully isolated.
Deletion & erasure
You can withdraw consent or request erasure at any time. Erased data is excluded from future training within our committed SLA, and affected model versions are queued for retrain and deprecation. One honest limit: already-shipped open weights can’t be retroactively scrubbed — which is exactly why old versions age out as new ones ship. The full terms live on the consent page and in the DPA.