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Humaniq

v.systems

George Connolly is the founder and CEO of OneLedger and a Forbes top 100 executive member and specializes in Systems Integration. George has worked as Private sector System Integration Technology Leader 15+yrs, PwC Technology Leader; Commonwealth Business Council - Government National Strategic Plan Consultant, Global ECM/Digital Transformation Leader.

George has established deep relationships with decision-makers across the Caribbean, and Central America can thrive in closing business and creating opportunities throughout the value chain.

He is known for innovative solution sales, marketing, advertising, and promotional strategies that focus on a point and deliver the desired results.

OneLedger

The Suterusu Protocol is a second-layer private payment infrastructure for smart contract platforms. The Suterusu Protocol uses the original and most advanced ZK-ConSnark algorithm that does not require a trusted setup. The algorithm’s proof size is significantly reduced and the proof generation and verification efficiency are greatly improved compared with similar solutions. Since no trusted setup is required, it is safe and transparent. The technical paper has been accepted by Eurocrypt 2021(https://eurocrypt.iacr.org/2021/acceptedpapers.php, https://eprint.iacr.org/2021/540). The Suterusu Protocol has been deployed on Ethereum, Binance Smart Chain, Heco, SmartBCH (BCH sidechain), Theta, etc. We plan to deploy Suterusu protocol on the following smart contract platforms including Near, Solana, Avalanche, Moonbeam, Plasma, Matic, etc. It is also the first privacy project funded by the official Cypherpunk Guild Fund of Near. We are also applying for the Solana and Polkadot ecosystem grant. The Suterusu Protocol intends to build a private payment infrastructure for any cryptocurrency. The Suterusu project has received investment from well-known institutions such as Dialectic (a fund founded by the former Polychain partner Ryan Zurr), Fundamental Labs, FBG, Continue Capital, DeFi Alliance, and other well-known institutions.

suterusu

TE-FOOD

High Performance Blockchain is the first permissionless public blockchain to innovate with hardware acceleration and provably random numbers:

acceleration delivers fast, ultra low-fee, on-chain transactions

provably random numbers support 100% fairness

HPB (the coin) is used to pay transaction gas fees and to reward node operators.

Hyperblox

BABB is a London-based FinTech company that provides accessible financial services to individuals worldwide. It uses blockchain technology to create peer-to-peer banking solutions, e-money accounts, and crypto-wallets. The BABB app offers seamless financial management, global money transfers, and access to banking services – all with a focus on empowering financially underserved communities.

ReDeFi: A Subsidiary of BABB

ReDeFi is an FMI platform designed for regulated financial institutions like banks, financial institutions, e-commerce and governments. It utilises a layer-1 and layer-2 model to facilitate the secure and compliant issuance of Onchain Money.

BABB

KAI Network is a next-generation blockchain designed to turn AI breakthroughs into on-chain value. It enables developers, content creators, prompt engineers, and researchers to earn $KAI by discovering novel techniques—such as prompts, workflows, model exploits, or parameter optimizations—and minting them as digital assets. These discoveries become NFTs (called DCVRs) that generate royalties and can be licensed or traded across the ecosystem.

Whether you’re building tools, running agents, or just experimenting with AI, KAI lets you capture the value of your creativity—directly, transparently, and on-chain.

KaiChain

QuadrantProtocol

GoChain

CyberVein's big-data solution is based on the PISR (private, interlink, secure, robust) distributed database, database operations are stored on CyberVein blockchain network which runs on a Proof-of-Contribution (PoC) consensus mechanism. The solution is focusing on enterprise-level "blockchain + big-data" customized services.

CVT is the native utility token that is used for:

Storage payment: The data owner pays the corresponding storage fee based on the file size and bandwidth consumed in such a process.

Computing power payment: Payments from user to owner for usage, and remuneration for software developers is going to be exclusively conducted in CVT.

Data exchange: On CyberVein's federated learning platform, the data acquirer trades the data at a price contracted between the two parties for distributed modeling applications.

CROSS NFT issuance payment: Dapp businesses are obligated to pay for Storage and Data Exchange in light of network resources occupied, and may set up CyberVein token as a means of payment to issue NFT or conduct business in accordance to their desired business model.

CyberVein tools include:

PISR Consortium database, creates better data management: through safe and reliable virtual machine operation and maintenance of user data, data is efficiently aggregated for upstream data, and data traceability and tracking are realized to ensure the reliability of data sources and outputs, and achieve cross-level, cross-departmental data sharing to improve the timeliness, diversity, stock and density of data to realize the commercial value of data, and truly solve the problems in data flow.

DAG storage chain, creates safer data storage, with better efficiency, no block confirmation, low transaction fees, and also eliminates miner, supports asynchronous verification and parallel processing of each node, the more nodes, the faster the speed, the stronger the scalability, which leads to better scalability. The database backup on DAG storage chain provides an extra layer of security for businesses.

Cytrix, allows GPU to be shared. Nodes can contribute part of their GPU to the network, in return for compensation through the Proof of Contribution mechanism. The contributed GPU can aid enterprises or individuals in data modeling with federated learning.

Federated Learning Platform, enables data to be monetized. Federated Learning is a distributed machine learning workflow. The datasets are first trained locally, and the data of all parties is kept locally, without revealing privacy or violating regulations.  Individual terminals return trained models to the server to create a shared model. Effectively protect data privacy and security, solve the problem of information silo, and thus realize the value of data. The platform will also provide algorithms to support data modeling operations by enterprises and individuals.

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