OpenLedger

• OpenLedger is a Layer 2 for decentralised AI development and data monetisation.

• Contributors build shared datasets called Datanets and are rewarded when models trained on them are used.

• OPEN is used for gas, staking, rewards and governance.

• Supply allocated across community, ecosystem and contributors.

• Rewards data and model contributions proportionally to their measured impact.

Pros:

• Attribution of contributions to model outputs is a genuine technical challenge being addressed.

• Community-owned datasets give contributors ongoing rather than one-time compensation.

• Built as a Layer 2 rather than a standalone chain, inheriting Ethereum security.

Cons:

• Measuring how much a specific data contribution affected a model output is technically contested.

• Demand depends on developers paying for attributed data.

• Crowded decentralised AI field.

• Exposure to attributed AI data and model infrastructure.

• Ethereum Layer 2 rather than a separate security assumption.

• Weigh the technical difficulty of attribution and whether buyers will pay.

• Contribution attribution recorded on-chain, so data providers are compensated each time a model trained on their work is used.

• Data contributors are paid once if at all, while models trained on their work generate revenue indefinitely.

• Recording attribution enables recurring compensation, if attribution can be measured credibly.

• Founded by Ram Kumar and colleagues.

• Backed by Polychain, Borderless Capital and HashKey.

• No public ICO. Distributed via Binance ecosystem programmes and airdrop in 2025.

• Attribution measurement is technically contested.

• Buyers may not pay for attributed data.

• Crowded decentralised AI segment.

• Early stage with limited production usage.