Omniscience

Omniscience

Omniscience combines advances in applied mathematics, systems engineering, distributed programming and advanced algorithms, to make high fidelity, high stakes decisions.

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$350k

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Revenues, earnings & profits over time
USD2019202020212023
Revenues0000000000000000
% growth-32 %--
EBITDA0000000000000000
Profit0000000000000000
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EV / EBITDA00.0x00.0x00.0x00.0x
R&D budget0000000000000000

Source: Dealroom estimates

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Omniscience Corporation operates at the intersection of complex data analysis and artificial intelligence, providing a platform to decipher hyperdimensional datasets without approximations. The company's technical foundations are rooted in the founders' experiences with the US intelligence community and in developing large-scale internet applications. This background led to the creation of the Omniscale computing model, which utilizes mathematical transformations and distributed computing to address high data volumes and combinatorial complexity.

The firm primarily serves the financial services and insurance industries. Its software suite is designed for professionals such as underwriters, quants, risk managers, and data scientists, enabling them to automate complex decisions. For the life insurance sector, Omniscience offers a product to automate underwriting. The business model is centered on providing this software to large enterprises, including insurers and reinsurers, to help them grow market share, reduce costs, and ensure regulatory compliance. Investors in the company include Reinsurance Group of America, TD Bank, Translink Capital, and The Guardian Life Insurance Company of America.

Founded by CEO Sunil Rawat and CTO Manu Shukla, the company is headquartered in Palo Alto, California. The leadership team has extensive experience in machine learning, finance, and data science. Since its inception, Omniscience has secured $13.7 million in funding over three rounds, with its largest being a $12 million Series A round in March 2020.

The core offering is a platform that can handle and interpret intricate, high-dimensional data, a capability that allows clients to make more accurate business decisions and identify new opportunities. By replicating the decision-making processes of experienced professionals in software, the platform aims to significantly speed up complex decisions. Its products include a Decision Engine and Document AI, which are part of the broader Risk Ops Platform. Keywords: hyperdimensional data, decision automation, financial services technology, insurance technology, insurtech, risk management software, underwriting automation, computational insurance, data analytics, artificial intelligence, machine learning, distributed computing, regulatory compliance technology, big data solutions, quantitative analysis tools, financial modeling, enterprise software, Palo Alto startup, Sunil Rawat, Manu Shukla

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