ORO is a human intelligence protocol that allows individuals to securely contribute their data to AI development while earning token rewards. It uses privacy-preserving technologies like zero-knowledge proofs and TEEs to anonymize data, ensuring AI models improve without compromising user privacy or fair compensation.
Funding
$6M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
0LACNFODFounders
Product
Problem
The advancement of artificial intelligence is constrained by the limited availability of high-quality, private data. AI companies have exhausted publicly available datasets, necessitating access to proprietary user data for further model development. However, current methods for data acquisition often compromise user privacy and fail to provide equitable compensation for data contributors.
Solution
ORO operates as a human intelligence protocol that enables individuals to securely contribute their data to AI development initiatives. Users engage in data-gathering activities, such as completing quests or linking social accounts, to earn ORO points. These points are then converted into token rewards, compensating users for the value their data generates. The platform employs privacy-preserving technology, including zero-knowledge proofs and trusted execution environments (TEEs), to anonymize data and ensure that AI models improve without direct access to raw personal information. This approach maintains data integrity and scarcity while protecting user privacy and facilitating fair compensation.
Target Audience
Individuals seeking to contribute their data to AI development and earn rewards, as well as AI companies requiring secure and privacy-compliant access to diverse datasets.
Features
- Human intelligence protocol for secure data contribution to AI advancements.
- User rewards system based on ORO points earned through data-gathering activities.
- Privacy-preserving technology utilizing zero-knowledge proofs (zkTLS) and Trusted Execution Environments (TEEs).
- Data anonymization and encryption to protect personal information.
- On-chain validation and scoring mechanisms for transparency and trust.
- Ability to link social and other accounts for data contribution.
- In-app quests and engagement activities to earn points.
- Token-based reward system for data value compensation.