Irys Raises $10 Million in Series A Funding Round

Irys, a programmable datachain, successfully raised $10 million in a Series A funding led by CoinFund, elevating its total funding to $20 million.

This funding aims to address inefficiencies in the $3 trillion data economy by enabling monetization at the protocol layer, impacting the future of data management.

Programmable Data Chains: Innovations and Challenges Ahead

The programmable datachain Irys announced an impressive $10 million Series A funding round led by CoinFund, with participation from Hypersphere, Tykhe Ventures, and others. This brings Irys’s total funding to $20 million, fostering scalability in their mission to revolutionize the data economy.

Data creators could gain new monetization avenues through Irys’s infrastructure, which intends to transform static data into economic assets. The raised funds are expected to drive the development of smart contract-driven licensing tools, enhancing data asset usage and efficiency.

“AI companies scrape trillions of dollars worth of content while creators see nothing… We’re building the infrastructure that finally allows data creators to capture the value they generate, turning data that historically is stored statically, into programmable economic assets.” — Josh Benaron, CEO & Founder, Irys

Market Insights and Expert Opinions

Did you know? Irys’s funding highlights possibilities for the data economy, reminiscent of early growth patterns seen with blockchain projects like Ocean Protocol.

Ethereum (ETH), currently valued at $4,214.62, holds a market cap of $508.74 billion and a market dominance of 13.34%, according to CoinMarketCap. Notably, ETH’s 24-hour trading volume experienced a significant decline of 30.58%, with price adjustments recorded at -2.91% over the past 24 hours.

Insights from Coincu’s research team suggest that Irys’s advancements could pave the way for a new wave of data monetization opportunities. Potential regulatory challenges could also arise, given the innovative nature of programmable datachains and their impact on traditional data usage models.