Ex-Google DeepMind leaders bring Reliant AI out of stealth with $15.4-million CAD seed round

Reliant AI Founders
Yoshua Bengio-backed startup wants to help biopharma researchers wrangle their data faster.

Montréal and Berlin, Germany-based data processing software startup Reliant AI has officially launched out of stealth and announced it has raised $15.4 million CAD ($11.3 million USD) in seed funding.

The round was co-led by Inovia Capital and Seattle-based Tola Capital, with participation from angel investor and former Cisco chief strategy officer Mike Volpi. In a statement, Reliant AI said it has raised 18.4 million CAD ($13.5 million USD) in funding to date, with other investors including former Datadog’s Amit Agarwal and Canadian AI pioneer Yoshua Bengio, who both participated in a prior round last fall.

Reliant AI plans to use the funding to hire engineering talent and expand its footprints in Europe and North America. 

Reliant AI says it is developing generative AI-powered data analytics software, initially targeted to the bio-pharmaceutical industry. The startup was co-founded by CEO Karl Moritz Hermann, chief scientific officer Marc Bellemare, and head of commercial Richard Schlegel. Bellemare

Hermann and Bellemare were previously senior research scientists at DeepMind, the AI research lab of Google, according to their LinkedIn pages.

Prior to joining Google, Hermann co-founded and led Dark Blue Labs, which was acquired by DeepMind in 2014.

Bellemare is also a Google Brain alum, has worked at Montreal AI institute Mila, and is an AI chair of the Canadian Institute for Advanced Research, which is leading part of the implementation of the Pan-Canadian Artificial Intelligence Strategy. Schlegel, for his part, was once a director at EY-Parthenon, the global strategy consulting arm of Ernst & Young. 

Reliant AI’s first product, Reliant Tabular, is designed to help life science analysts find scientific evidence for their decisions through automated systematic reviews, asset scans, analyses, and a data platform.

“The sheer amount of menial labor involved in data-intensive industries today means that many highly skilled professionals are focused on wrangling data, rather than solving complex issues,” Hermann said in a statement. He said the AI system is specific to the life sciences and will be able to “radically grow its capacity to perform research at scale.”

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In its statement, Reliant AI said the Tabular offers machine learning models that are “optimized to be experts” in biopharma topics, an easy user interface, and answers in a report-ready format.

On its website, Reliant AI claims the product allows researchers to perform asset scans 4.8 times faster than by hand, and makes 10 times fewer errors than the average analyst or general purpose AI software.

“We see a significant market opportunity in the pharmaceutical sector, as companies strive to build and partner with new entrants to develop innovative solutions like those offered by Reliant AI,” Steve Woods, partner at Inovia Capital, said in a statement. “This notable demand in a large and growing market underscores the potential of AI to drive impactful advancements in the biopharma industry.”

Reliant AI plans to use its seed funding to hire engineering talent and expand its footprints in Europe and North America. 

TechCrunch reported today that the startup has chosen to buy its own AI hardware instead of renting from a larger provider, and is now focused on proving that its technology can pay for itself.

The company’s first product is currently available for demo. A spokesperson for Reliant AI told BetaKit the company is currently developing the application with select partners, is seeing recurring usage of the platform, and is looking to expand to a “substantially larger” customer base later this year.

Feature image courtesy of Reliant AI.

Isabelle Kirkwood

Isabelle Kirkwood

Isabelle is a Vancouver-based writer with 5+ years of experience in communications and journalism and a lifelong passion for telling stories. For over two years, she has reported on all sides of the Canadian startup ecosystem, from landmark venture deals to public policy, telling the stories of the founders putting Canadian tech on the map.

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