(( draft ))

Quality control

Systems, that require Sybil resistance and rely on human verification methods, may quality control those methods. They can discover price-of-forgery for each method they use.

An example integration and price of forgery discovery workflow are described in this issue (originally for Gitcoin, but will fit many).

Score providers/consumers/prosumers


With any human verification method can be monetized. Upala can be wrapped around any existing identity system or human verification method, help discover its price of forgery and make it's score compatible with all other systems that use Upala. The more human verification there are in the system, the higher the aggregated scores user can achieve. Also read on Bladerunner DAO to see how Upala breaks competition between identity systems.


DApps may select score providers they trust. Then they set a threshold Upala score. Users whose score is above the threshold may get additional benefits. This way DApps may protect value that otherwise could be extracted from them by bots.

Prosumers and aggregators

DApps may digest the scores they use from their score providers, refine them with their own user behavior data and start providing that refined score.

Identity bridge

Identity systems which are off Ethereum main-net may create Upala groups and instantly make their scores available on Ethereum. When Upala becomes cross-chain that would mean even greater interoperability.


Lending platforms may require Upala ID as a collateral. The user ID is staked. If the user cannot payout, the ID is exploded by lending platform.


But there's a way to provide Upala info to the web2 world (and real world too).

That's inverted oracles. Like infura or graph protocol, but for web2.

They can try to create their own monetization.

Use cases from CAPTCHA (perfect with Login with Ethereum concept)