Etherparty

by Etherparty

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FLO

by FLO

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Zilliqa

by Zilliqa

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Etherparty

by Etherparty

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FLO

by FLO

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Zilliqa

by Zilliqa

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What problem does this service solve?

Etherparty wants to simplify the development of decentralized applications. It is developing a platform of blockchain software products that will help users develop many of the common functionalities with less technical knowledge.FLO's blockchain allows users to record short comments or notes to its transactions.Zilliqa is building a scalable development platform based on sharding.

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Company Description

Etherparty is a cloud platform offering blockchain related software. They want to make smart contracts as easy and accessible as possible. by helping to automate many functions that decentralized applications require. Etherparty focuses on user-friendly design to simplify the creation of smart contract related platforms. They are currently developing several software products aimed at users with different needs, including: token generation, crowdfunding, supply chain management, and philanthropy. Etherparty is powered by FUEL tokens.

FLO is a Proof-of-Work blockchain with a metadata layer called floData. It enables users to easily record notes to its blocks, and can be used to create DApps. One of FLO's central features is the Open Index Protocol, which standardizes cryptographic ownership on open networks. The founders of FLO are also working on Alexandria; an open-source standard for users to publish and distribute original content. FLO's source code is based on that of Bitcoin and Litecoin. It is designed to enable fast transactions times.

Zilliqa is an innovative blockchain platform that is designed to be more scalable as the network grows. Zilliqa's platform is based on the concept of sharding; which involves breaking a large network of computers into smaller decentralized networks.
Zilliqa's goal is to increase transaction rates as its network expands. The platform is tailored towards enabling secure data-driven decentralized apps that are designed to meet the scaling requirements of machine learning and financial algorithms.

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