Secures $8 Million to Enhance AI Usage in Investment

The platform already has dozens of clients on-board., a distributed machine learning platform for investment professionals, has announced on Tuesday the closure of its Series A funding round, raising $8 million.

The funding round was led by Portag3 Ventures and was participated in by Dunamu & Partners and Polar Equity Partners.

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Founded in 2017, the Toronto-headquartered company is targeting asset managers, mutual funds, hedge funds, family offices, and investment arms of commercial banks, with the machine learning-based products, augmenting the process of investment.

According to the company, it has on-boarded dozens of clients on its platform, whose combined asset under management (AUM) is over $500 billion.

“According to the CFA Institute, there are five main hurdles to using artificial intelligence within investment management: cost, talent, technology, vision, and time. Boosted Insights solves all five hurdles for managers,” Joshua Pantony, CEO of, said in a statement.

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“Our mission is to bring elements of quantitative management to the finance industry at large as data becomes the difference between winning and losing for investors globally.”

Streamlining services to attract more clients

The announcement detailed that the fresh capital will be utilized to enhance its flagship platform – called Boosted Insights. The AI-based platform allows idea generation, portfolio construction, and portfolio monitoring in a simplified environment.

The proceeds will also be used in increasing manpower in its office, as well as in marketing and sales processes.

“Quantitative overlays, factors, and stand-alone strategies are no longer options for the investment management industry – they are a requirement to compete. The challenge the industry faces is systematically and efficiently implementing them, alongside unique data sources, to stay ahead of the competition,” Adam Felesky, CEO of Portag3 Ventures, added.

“The platform enables asset managers of any sophistication to do this by tapping into the most advanced machine learning tools available, augmenting their existing investment process through a user-friendly interface that does not require coding expertise.”

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