Nasdaq-listed CIMG Inc. has partnered with FLock to develop an AI-powered wellness product that leverages FLock’s federated learning technology, while also exploring a potential acquisition of FLOCK tokens.
Summary
- The LifeNode product will leverage FLock’s federated learning and privacy-preserving technology to enable secure AI-assisted wellness monitoring and recommendations without centralizing user data.
- CIMG is also exploring a potential acquisition of FLOCK tokens for its digital asset treasury.
- CIMG faces regulatory and financial challenges, including a Nasdaq delisting notice due to non-compliance with minimum bid price requirements.
CIMG Inc., a Nasdaq-listed micro-cap company focused on digital health and sales development, has signed a non-binding MoU with FLock Technology Holdings to develop an AI-powered wellness monitoring and recommendation product called LifeNode. Under the agreement, FLock will serve as CIMG’s provider of privacy-preserving AI technology for the product.
“Our partnership with CIMG marks a strategic step forward in expanding our privacy-preserving AI capabilities from clinical and institutional healthcare into the consumer health and wellness space,” said Jiahao Sun, Chief Executive Officer of FLock.
The MoU also outlines a potential acquisition of FLOCK tokens to be added to CIMG’s digital asset treasury.
CIMG and FLock.io look to use AI models more broadly
For CIMG, the development comes as the firm is facing regulatory and financial challenges, including a delisting notice from Nasdaq. The company remains non-compliant with the minimum bid price requirement under Nasdaq Listing Rule 5550(a)(2) and is ineligible for a second extension after failing to meet the original deadline. A hearing is scheduled for August to address the potential delisting.
For FLock, the MoU with CIMG follows an earlier major move, namely its appointment as the sole decentralized AI training partner for the Hong Kong Generative AI Research and Development Centre , where it will leverage FLock’s federated learning to develop AI models for government and public sector applications.
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