Polkadot Blockchain

by Web3 Foundation

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Mercury Token

by Sigwo Technologies

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Seele

by Seele Foundation

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Polkadot Blockchain

by Web3 Foundation

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Mercury Token

by Sigwo Technologies

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Seele

by Seele Foundation

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What problem does this service solve?

Polkadot aims to improve interoperability and overall performance for DApps running across multiple networks.The Mercury Token aims to allow users to create DApps on the Jupiter platform that can interact with the Waves blockchain.Seele wants to create a blockchain ecosystem comprised of subnets that operate independently, but will have cross-chain capabilities.

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Company Description

The Polkadot blockchain is a multi-chain blockchain that is designed to bundle multiple chains together so that they can be executed in parallel. The goal is for every block on the Polkadot blockchain to contain multiple blocks from other chains. This will enable the network to contain the transaction information from multiple chains and dramatically increase the overall interoperability between different blockchain networks. Polkadot was created by the Web3 Foundation, which is led by Gavin Wood, one of the founders of Ethereum. Polkadot is their flagship project, and aims to solve the issues in the blockchain ecosystem related to disjointed governance and interoperability.

Mercury Token is a Waves-based token that was created to facilitate cross-chain communication, and timestamping, between the Waves blockchain and the Jupiter blockchain.

Seele is developing a blockchain ecosystem that will consist of subnets optimized for different use cases. Seele's Forest Network will have subnets that will operate independently and can interact with each other through cross-chain and cross-domain protocols. Seele has a neural consensus algorithm that was inspired by the inner workings of the human brain. It asynchronously processes and sorts data in a large-scale decentralized environment, using ε-differential agreements to allow all nodes within a network to reach consensus. Compared to existing consensus algorithms, it ensures greater fault-tolerance and is significantly more efficient. Its performance also scales linearly as network size increases, allowing it to be widely adaptable to many different use cases.

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