Bayesline is a GPU-powered financial analytics suite for institutional investors headquartered in New York City [1][4]. Founded in 2024 [5], the company provides highly customizable and blazingly fast analytics for asset managers [1]. The platform enables clients to build custom analytics in seconds through a cloud-deployed solution, addressing frustrations with off-the-shelf offerings [2]. Bayesline was founded by Sebastian, a CFA with experience as a Bloomberg Quant and AI Research professional, and Misha, a PhD and former BlackRock Managing Director, who met while working at BlackRock in 2016 [2]. The company is Y Combinator-backed, part of the Summer 2024 batch [3], and operates with a team of three [6].
About
- Bayesline is building a GPU-powered financial analytics suite for institutional investors, like hedge funds. Clients use our cloud deployed solution to build custom analytics in seconds, having previously been frustrated with off the shelf solutions that don't generate any alpha. What used to take weeks or months now happens near instantly. Sebastian, CFA (ex Bloomberg Quant & AI Research) and Misha, PhD (ex BlackRock Managing Director) met while working at BlackRock in 2016. With a combined 20 years of experience in the space they set out to change the way the industry uses analytics - from one size doesn't fit all to truly tailored to clients' needs.[2]
- Bayesline is building a GPU-powered financial analytics suite for institutional investors, like hedge funds. Clients use our cloud deployed solution to build custom analytics in seconds, having previously been frustrated with off the shelf solutions that don't generate any alpha. What used to take weeks or months now happens near instantly. Sebastian, CFA (ex Bloomberg Quant & AI Research) and Misha, PhD (ex BlackRock Managing Director) met while working at BlackRock in 2016. With a combined 20 years of experience in the space they set out to change the way the industry uses analytics - from one size doesn't fit all to truly tailored to clients' needs.[11]
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