QuickNode raised 60 million USD

Blockchain infrastructure provider QuickNode announced that it has raised $ 60 million at a valuation of up to $ 800 million.

QuickNode raised 60 million USD

QuickNode, a blockchain infrastructure company, held a $60 million Series B funding round at an enterprise valuation of $800 million. The list of large funds participating in the funding round includes 10T Holdings, Seven Seven Six, Tiger Global, etc.

Founded in 2017, QuickNode specializes in providing development tools on 16 different blockchains to large organizations, with prominent clients including BNY Mellon, Samsung, LG, Coinbase, Chainalysis, Nansen, Dune Analytics, Dapp Radar and 1inch Network.

QuickNode CEO Alex Nabutovsky revealed that the funding round was started in September 2022 and ended in December, a time when the cryptocurrency market has experienced a lot of volatility since the collapse of the FTX exchange.

The CEO confidently asserted that he did not face many obstacles in the process of raising money because “the business and the demand for QuickNode’s services are constantly increasing”. The company’s revenue last year increased 300% compared to 2021, with two record quarters in the second half of 2022.

The valuation of this Miami-based company (USA) also increased rapidly. In October 2021, the company raised $35 million at a valuation of $250 million. For comparison, QuickNode’s competitor Alchemy in February 2022 raised capital at a valuation of up to $ 10.2 billion.

With the new money raised, QuickNode plans to expand its staff from 120 to 180 people, as well as open more branches in Australia and Asia.

CEO Alex Nabutovsky also announced plans to issue a governance token to decentralize QuickNode in the near future, but before that could do a Series C funding round.

Synthetic Kyptos

Stay in the Loop

Get the daily email from CryptoNews that makes reading the news actually enjoyable. Join our mailing list to stay in the loop to stay informed, for free.

Latest stories

- Advertisement - spot_img