IAGON has completed its funding round to build Cardano’s first decentralized big data platform. The startup has raised $3.4 million in seed and private funding from respected crypto enthusiasts and mutual funds.



LedgerLink Labs led funding round attended Blockchain Israel, AU21 Capital, Kirin Fund, Coinsgroup, Cinchblock, Panony, X21, Genblock, Alphabit, Launchpool, GBV Capital, Trustdao Network, Faculty Group, Llamas, BH Investments, Next Chymia Consulting and many more .

The company states that they aim to build a scalable platform that leverages blockchain technology and consolidates big data for the first decentralized storage network in Cardano. An Ethereum deployment of the same model is already in progress.

Co-founder Navjit Dhaliwal expressed his satisfaction with the participation with these words:

We are excited to have the support of such a large network of investors in the crypto ecosystem, especially focused on Cardano.

IAGON Business Advisor Darren Camas said, “With support from both the enterprise and grassroots crypto community, we stand ready to be a decentralized alternative to AWS and all other Big Tech cloud infrastructures.”

Cloud computing has changed the cost structure and model of building systems and networks. IAGON’s vision is aligned with the decentralized ethos of creating a distributed market for computing and storage resources.

He also added:

The IAGON team is also embracing the third way that decentralization and regulation can be harmonious. Openness and decentralization as we develop tools that will ultimately prevail, tools that the end user can choose for their particular use case and personal use based on medical records and legal requirements such as HIPAA compliance in the US or GDPR in the EU or data ownership or cross-border customer data transfer embracing systems.

Once launched, IAGON will enable the storage of all types of files, including large repositories and large media files as well as smaller files. However, while offering secure computing, resource-intensive tasks can also be processed in the decentralized cloud using artificial intelligence and machine learning.


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