FLock.io Teams Up With Walrus Protocol And Sui Foundation To Advance Decentralized, Privacy-Preserving AI On Sui Network

In Brief

FLock.io has partnered with Walrus Protocol and the Sui Foundation to build a decentralized, privacy-preserving AI training infrastructure on the Sui Network.

Decentralized platform aiming to enhance AI model training through the use of federated learning and blockchain technology, FLock.io announced a strategic collaboration with decentralized blob storage and data availability layer Walrus Protocol and the organization dedicated to supporting and driving the adoption of the Sui blockchain, Sui Foundation to advance decentralized, privacy-preserving AI across the Sui Network ecosystem.

As part of this initiative, Walrus’s decentralized data infrastructure and SEAL’s encryption framework will be integrated into FLock’s federated learning architecture. This allows for the secure training of AI models in a manner that supports community ownership and eliminates the need for centralized data sharing.

FLock’s approach utilizes federated learning to enable distributed model training without exposing raw user data. To expand this process securely, the platform requires decentralized mechanisms for broadcasting, storing, and encrypting model updates.

The integration of Walrus and SEAL provides this capability. Walrus will function as the foundational infrastructure for FLock’s Federated Learning Alliance—a network of nodes that collaboratively train models. It offers decentralized methods for transmitting and storing model gradients, parameters, and outputs, thereby removing reliance on centralized servers and eliminating single points of failure.

SEAL contributes programmable encryption and access control measures to the system. It restricts visibility and participation in each training round to verified contributors, ensuring that data remains encrypted throughout the process and can be stored and accessed without requiring trust in any specific server or intermediary.

Together, Walrus and SEAL address key gaps in building secure and decentralized federated learning pipelines. This advancement supports FLock’s objective of scaling its Federated Learning Alliance, enabling wider participation among developers while maintaining privacy and decentralization by default.

This collaboration forms part of a broader effort to establish a secure, modular, and community-driven AI infrastructure. As part of the roadmap, FLock.io is working with the Sui Foundation to refine an open-source foundation model tailored for agentic AI applications within the Sui ecosystem.

FLock.io Partners With AIGEN Sciences To Bring Privacy-Preserving AI Infrastructure To Drug Discovery

FLock.io provides an infrastructure that facilitates collaborative training of AI models among distributed participants while preserving the privacy of individual data sources. The platform integrates blockchain-based reward systems to deliver transparent and verifiable compensation for contributions made throughout each phase of model development.

Recently, FLock.io disclosed a strategic partnership with AIGEN Sciences aimed at deploying its privacy-focused AI framework within the domain of drug discovery, supporting secure and decentralized innovation in biomedical research.