Roles and how they earn
| Role | Earns from | Why they matter |
|---|---|---|
| Contributors | Royalty share via ownership fractions | Create verified knowledge units |
| Validators | Validation fees and royalty share where policy allows | Keep quality high and fraud low |
| Backers | Share of owner returns when underwriting cohorts or datasets | Finance data creation and smooth income |
| Buyers | Better models, lower upfront cost with TNPL | Demand side of the flywheel |
Reputation
A transparent score derived from credentials, historical accuracy, volume and timeliness, and stake behavior.The score maps to a reward multiplier with a safe band, for example
0.8x to 1.3x.
Staking for confidence
| Stake type | Token | What it does | Slashing signals |
|---|---|---|---|
| Stake on data | $XNY | Acquire or boost ownership fractions of an asset or cohort | Proven inaccuracies, failed audits |
| Stake on contributor | $XNY | Back a person or team to lift their reputation multiplier | Systematic low accuracy, fraud, failed KYC escalation |
Both stake types are protocol-level. They secure the network, align incentives, and gate premium tasks.
Quality controls
- Randomized checks against ground truth, adversarial spot audits
- AI assisted review and facial or KYC escalation where policy requires
- Dispute ladder with bonded challenges and transparent outcomes