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Thursday, August 26, 2021

Monad emerges from stealth with $17M to solve the cybersecurity big data problem

Cloud security startup Monad, which offers a platform for extracting and connecting data from various security tools, has launched from stealth with $17 million in Series A funding led by Index Ventures. 

Monad was founded on the belief that enterprise cybersecurity is a growing data management challenge, as organizations try to understand and interpret the masses of information that’s siloed within disconnected logs and databases. Once an organization has extracted data from their security tools, Monad’s Security Data Platform enables them to centralize that data within a data warehouse of choice, and normalize and enrich the data so that security teams have the insights they need to secure their systems and data effectively.

“Security is fundamentally a big data problem,” said Christian Almenar, CEO and co-founder of Monad. “Customers are often unable to access their security data in the streamlined manner that DevOps and cloud engineering teams need to build their apps quickly while also addressing their most pressing security and compliance challenges. We founded Monad to solve this security data challenge and liberate customers’ security data from siloed tools to make it accessible via any data warehouse of choice.”

The startup’s Series A funding round, which was also backed by Sequoia Capital, brings its total amount of investment raised to $19 million, and comes 12 months after its Sequoia-led seed round. The funds will enable Monad to scale its development efforts for its security data cloud platform, the startup said.

Monad was founded in May 2020 by security veterans Christian Almenar and Jacolon Walker. Almenar previously co-founded serverless security startup Intrinsic, which was acquired by VMware in 2019, while Walker served as CISO and security engineer at OpenDoor, Collective Health and Palantir.



https://ift.tt/eA8V8J Monad emerges from stealth with $17M to solve the cybersecurity big data problem https://ift.tt/2WjpmjL

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