MultiversX

MultiversX

Layer-1 blockchain with scalable smart contracts

Overview

MultiversX is a layer-1 blockchain network designed for scalable, secure, and developer-friendly decentralized applications. It runs as a decentralized system with many nodes and uses its native token EGLD to pay for transactions, run smart contracts, and reward validators. The platform provides sovereign blockchain modules and core apps that individuals and businesses can use to build and deploy dApps, aiming for high throughput and low latency. Compared with other smart contract platforms, MultiversX emphasizes scalability and a modular, developer-focused environment that supports enterprise and Web3 applications. Its goal is to enable fast, reliable blockchain infrastructure for next-generation applications while maintaining a sustainable economic model around EGLD.

About MultiversX

Simplify's Rating
Why MultiversX is rated
C
Rated C on Competitive Edge
Rated C on Growth Potential
Rated C on Differentiation

Industries

Data & Analytics

Enterprise Software

Crypto & Web3

Company Size

51-200

Company Stage

ICO

Total Funding

$5.2M

Headquarters

Saint Julian's, Malta

Founded

2017

Simplify Jobs

Simplify's Take

What believers are saying

  • Ta-Da private beta on MultiversX rewards TADA tokens for AI training data.
  • Sovereign chains and Holochain integration boost P2P scalability.
  • Vivoka's 42-language voice data from 100 clients enhances AI datasets.

What critics are saying

  • Solana's 65,000 TPS diverts DeFi dApps, eroding EGLD demand in 6-12 months.
  • Sui's 297,000 TPS and Move language stagnate MultiversX TVL at #58.
  • Ethereum L2s like Base slash DeFi share with sub-cent fees in 3-6 months.

What makes MultiversX unique

  • MultiversX uses adaptive state sharding for 263,000 TPS peak throughput.
  • WASM virtual machine enables multi-language smart contracts.
  • Over 3,200 validator nodes ensure high decentralization.

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Funding

Total Funding

$5.2M

Above

Industry Average

Funded Over

3 Rounds

Ico funding comparison data is currently unavailable. We're working to provide this information soon!
Ico Funding Comparison
Coming Soon

Growth & Insights and Company News

Headcount

6 month growth

0%

1 year growth

2%

2 year growth

4%
BeInCrypto
Oct 3rd, 2025
xMoney Secures $21.5m Strategic Funding Led by Sui Foundation

xMoney, the payments company bridging stablecoins and global commerce, announced today that it has raised $21.5 million in strategic funding with the Sui Foundation leading the round.

The Defiant
Jan 30th, 2025
Pell Network Raises $6.5 Million for Omnichain Bitcoin Restaking and $3.5M for AI-driven DeFi, Starknet Advances ZK Technology

Pell Network has successfully raised $6.5 million to develop its omnichain Bitcoin restaking network

BeInCrypto
Feb 28th, 2024
5 Altcoins For March: Keep An Eye On These Potential Movers

Ethereum (ETH), MultiversX (EGLD), SEI, Astar (ASTR), and DUSK are all altcoins that have interesting developments lined up in March, which could positively affect their price. February was a bullish month for the cryptocurrency market, characterized by an ongoing increase that took several altcoins to new highs and Bitcoin (BTC) very close to an all-time high. The five altcoins below could draw considerable attention in March 2024. Ethereum Releases Dencun UpgradePrice: $3,305

InvestingCube
Jan 9th, 2024
Morningstar Ventures Leads $3.5 Million Funding For AI Firm Ta-Da

Ta-Da is expanding the potential of AI, and it uses a gamified Web3 app where users are incentivized to validate data

Decrypt
Sep 29th, 2023
Get Paid To Train Ai? There'S A New Cryptocurrency For That

Your Web3 Gaming Power-Up Enjoy exclusive benefits with the GG Membership PassDecrypt’s Art, Fashion, and Entertainment Hub. Discover SCENEBy merging Web3 and artificial intelligence, Vivoka is introducing a new way to collect data to train our robot overlords.Under the leadership of William Simonin and the voice-recognition acumen of Vivoka, the company has just rolled out the private beta for its new project “Ta-Da,” a play on the word data.ADADPublic beta is expected next quarter.“Through 'Ta-da,' we envision a platform where diverse AI firms, transcending just speech recognition, can requisition data, ensuring affordability without compromising on quality,” Simonin told Decrypt.Tapping blockchain technology, Ta-Da aims to encourage users worldwide to share data they will create by accomplishing various tasks like reading a sentence, writing a text, or recognizing an object.The collected data, which could include voice recordings, images, videos, and texts, will then be accessible to businesses for the purpose of AI model training.Users are then rewarded with TADA tokens for their contributions.Developed on the MultiversX blockchain, the platform aims to address key challenges faced by companies using data to train AI models, specifically those of high costs and inconsistent data quality.ADAD“We perceive blockchain providers as pivotal technical allies,” Simonin told Decrypt. “Collaborating with MultiversX feels more intimate and prioritized than being one amongst countless projects on alternative platforms."Ta-Da's model also prioritizes user privacy by relying solely on volunteer-generated data, a stark contrast with the practices of companies such as Meta and Amazon.Meta Platforms utilized public posts from Facebook and Instagram to train its Meta AI virtual assistant, while Amazon leveraged actual user conversations to refine Alexa's AI model.Ta-Da AI takes aim at diverse audio dataGiven the focus on voice recognition, one of Ta-Da’s main purposes is to amass voice recordings in myriad languages, all intended to fine-tune AI voice recognition systems.With Vivoka, William Simonin spent years crafting a tech solution supporting 42 languages and tailored for voice development kits, enabling businesses in diverse sectors like robotics and logistics to embed it within any speech interface.The firm currently works with approximately 100 global clients, and its technology is embedded in over 100,000 devices globally.It’s through this extensive work that he identified challenges within the nascent voice data collection sector.The immense volume of data required for refinement can be prohibitively expensive. The price tag for 1,000 hours of audio can cost as much as $100,000. It's common for companies focused on AI to allocate budgets ranging from $100,000 to $1 million annually just for this type of data.ADADFurthermore, concerns frequently arise regarding the data's authenticity and quality. "Only about 5-10% of a dataset undergoes rigorous examination," noted Simonin, drawing attention to challenges like inferior data quality and inadequate compensation for genuine contributors.The challenge remains in securing a diverse and expansive audio dataset, particularly when seeking to understand complex languages

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