← Use cases · ML researchers & model developers
A permissionless venue to ship detectors
If you build detection models, dfpn is the supply side of a verifiable-AI network: deploy your detector, and get paid when it contributes to a consensus verdict — no vendor gatekeeper.
The problem
A strong detection model usually reaches production only through a vendor relationship or an internal deployment. There is no open, incentive-aligned marketplace where a researcher can register a detector and earn whenever it contributes to a paid, verifiable verdict. dfpn is that marketplace — the model layer of a DePIN detection network.
Where dfpn fits
- ▸You have a detection model and want a permissionless place to deploy it
- ▸You want to earn when your model contributes to real verdicts
- ▸You want your model evaluated against rotating, hidden test sets rather than a static benchmark you can overfit
- ▸You want on-chain provenance for which models contributed to which verdicts
How the flow works
- 01
Register
Publish model metadata and a version to the Model Registry program and post the developer stake (20,000+ DFPN per version).
- 02
Get run
Workers run registered models as part of serving requests; your model contributes to consensus verdicts.
- 03
Earn
Collect a share of the 20% model-developer fee split whenever your model is used on a paid request.
Honest caveat
Model developers are held to the same honesty bar as workers: overfit or biased models are countered by hidden test sets and periodic benchmark rotation, and the developer stake is slashable.
Other use cases
Put it to work
Wire verdicts into your pipeline, or read how a verdict is produced end to end.