Transforming Industries
Decentralized AI applications span multiple sectors, each leveraging privacy-preserving techniques to unlock new capabilities.
Hospitals collaborate on AI models for cancer detection using federated learning, keeping patient data private.
Banks share fraud patterns through homomorphic encryption to improve detection without exposing customer data.
Vehicle fleets share driving data anonymously to improve autonomous navigation using secure aggregation.
Companies participate in shared forecasting models that improve accuracy without exposing proprietary data.
Research institutions collaborate on climate models using distributed sensor data from global IoT networks.
Educational platforms create personalized learning paths using private student data contributions.
Building on Ailoos
Empoorio's Ailoos platform provides the tools and infrastructure for developing privacy-preserving AI applications. From federated learning frameworks to zero-knowledge proof systems, developers can build compliant applications with built-in economic incentives.
Train models across distributed datasets without data sharing.
Prove model outputs and computations without revealing inputs.
Compute on encrypted data for confidential inference.
Tokenized Participation
DracmaS tokens power the economic layer of decentralized AI, rewarding data contributions, compute resources, model development, and long-term quality. Incentives align builders, validators, and data owners through transparent revenue splits, staking-based reputation, and verifiable contribution proofs.
On-chain attestations and ZK proofs validate work without exposing sensitive data.
Staked participation increases trust; poor quality or malicious behavior is penalized.
Model fees adapt to demand, accuracy, and latency requirements.
Token holders fund new datasets, research, and ecosystem grants.
Earn tokens for providing high-quality data to AI models, with staking mechanisms ensuring data integrity.
Share idle processing power and earn rewards for contributing to federated training rounds.
Pay for access to trained models, with revenue distributed to data providers and developers.
Stake tokens to vouch for data quality and model performance, creating reputation systems.
Build Your First AI Application
Start developing privacy-preserving AI applications on Empoorio with the Ailoos SDK and reference blueprints. Build pipelines that are verifiable, composable, and production-ready, from data ingestion to on-chain incentives and model distribution.
Ingest private data via federated learning or encrypted pipelines.
Choose templates, set evaluation metrics, and configure privacy constraints.
Publish on-chain, generate proofs, and expose endpoints for dApps.
Set fees, distribute rewards, and track usage in real time.