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3 Latest Announced Rounds

  • $3,500,000
    Seed

    1 Investors

    Technology, Information and Internet
    Dec 20th, 2024
  • $5,619,170
    Series B

    1 Investors

    Research Services
    Dec 20th, 2024
  • $8,000,000
    Unknown

    5 Investors

    Computer & Network Security
    Dec 20th, 2024
$671.88M Raised in 44 Funding Rounds in the past 7 Days - View All

Funding Round Profile

SirenOpt

start up
United States - Oakland, California
  • 26/07/2024
  • Seed
  • $6,600,000

SirenOpt is accelerating sustainable and smart manufacturing of advanced materials by delivering a manufacturing intelligence platform that uses intelligent characterization and real-time decision-making to drive the creation of innovative, high-performance products that fuel the advancement of society.

SirenOpt is pioneering a paradigm shift in materials manufacturing intelligence by leveraging cold atmospheric plasma, machine learning and predictive analytics to non-destructively create a uniquely distinctive, multifaceted material fingerprint in real-time. SirenOpt transforms measurement blind spots into rich multi-layered material insights, which enable intelligent performance-centric decision-making. SirenOpt thus accelerates R&D and process optimization, enhances product performance, and delivers higher production quality to maximize value in both in-line and off-line applications. SirenOpt’s manufacturing intelligence platform has demonstrated use cases across battery, aerospace, semiconductor, electronic and many other advanced manufacturing segments in both inline production and offline tool deployments.

SirenOpt was founded in 2022 as a spin-out from the UC Berkeley Chemical Engineering Department. SirenOpt is supported by the UC Berkeley Skydeck, Lawrence Berkeley National Laboratory Cyclotron Road and Activate science-driven startup accelerator programs.


Related People

Jared O'LearyCo Founder

Jared O'Leary United States - Oakland, California

Chemical engineer with expertise in learning-based characterization, modeling, and control of stochastic systems. I am interested in leveraging the interplay between theory, computation, and application to enable cost-effective, sustainable, and high-performance manufacturing of advanced materials.