Data Collective, Other Top AI VCs, Pour $102M Into Element AI Series A

[Updated 6/14/17, 1:45 pm. See below.] Canada’s Element AI, publicly launched in October, announced today it has raised US$102 million in an outsized Series A financing round seen by experts as a sign that artificial intelligence is ready to solve real-world business problems.

The young Montreal-based company, whose staff of AI engineers collaborates with academic AI researchers, offers consulting services to businesses and also plans to co-found AI startups in the future. With founders that include Yoshua Bengio, co-founder and director of the prominent Montreal Institute for Learning Algorithms (MILA), Element AI’s big fundraising debut reinforces Canada’s claims as a competitive hub in the global development of AI technology.

The startup’s early trove of capital came from a roster of some of the most active investors in AI. The round was led by Data Collective, joined by Intel Capital, Nvidia, and Microsoft Ventures. The investor roll also reflected Canada’s ecosystem of financial backing for innovation. Development Bank of Canada, Fidelity Investments Canada, and early-stage venture capital fund manager Real Ventures joined in the round.

Observers in the AI field greeted the big Series A as proof of the technology’s practical uses in business, and the presence of research centers in many regions that are prepared to bring those solutions to life.

“Element AI is a good example of bringing AI research into the commercial world,” Krishna Gupta, founder and general partner at Boston-area venture firm Romulus Capital, wrote in an e-mail exchange with Xconomy.

“This round will not only elevate Montreal as a serious AI hub, but it will also lead to a greater flow of academic talent toward startups and larger technology companies, which inevitably will create more activity and hopefully more progress,” Gupta says.

Romulus has invested in AI startups that touch on the interactions between machine learning and human behavior: patient mood tracker Ginger.io; Humanyze, an office morale and productivity tool; and voice analytics startup Cogito.

Oren Etzioni, CEO of the Allen Institute for Artificial Intelligence in Seattle, says the Element AI deal showcases the role that startups, research labs, and non-profits can play in the development of AI, “independent from massive corporations.”

Element AI’s big fundraising round also confirms that “we’re starting to see that people understand how AI can be applied and monetized,” Etzioni wrote in an e-mail to Xconomy. “A few years ago, AI investments were smaller because it was difficult to understand the path of an AI company or technology, whereas today you know with some certainty that AI technologies developed the right way have a healthy marketplace to enter.’’

For Manoj Saxena, former general manager of IBM Watson’s Solutions in Austin, TX, and an investor who focuses primarily on AI startups, such a large funding round supports his belief that AI will become more pervasive than the Internet and “rival electricity in terms of civilization and business-morphing impact.”

Still, he cautions that the road to this future could be rocky for some AI companies. “The flip side is that this space is a very difficult one to crack as it involves bringing together an entire new category of software, data, skills, compliance/ethics, and organizational change to successfully implement and scale,” says Saxena, who is also executive chairman of Austin AI startup Cognitive Scale. [Saxena’s affiliation with Cognitive Scale added.] As a result there will be a lot of companies doing ‘science projects’ that will fail in the enterprise space.”

One of Element AI’s goals is to democratize AI by offering access to the technology to companies that can’t afford research staffs on a corporate scale. Together with the Montreal Institute for Learning Algorithms, Element AI developed a structure for collaboration with university researchers that has been used in several projects it has already tackled for companies.

“We have done projects in fintech, manufacturing, logistics, retail, cyber-security,” Element AI co-founder and CEO Jean-François Gagné (pictured) wrote in an e-mail to Xconomy. “We have not yet [created] spin-off startups as we are still early in the process but we think we will have a few opportunities to do so.”

In its early projects, the startup says, it has used neural network-based models to design a more efficient system to detect fraud and manipulation in the U.S. energy market; developed a better pricing algorithm for a property and casualty insurance company; and improved the scheduling of trucks arriving at “a busy North American port” to pick up or unload container ship cargoes, thereby reducing wait times and traffic congestion.

The company says it can apply artificial intelligence technology across functions including predictive modeling and forecasting, voice recognition, voice interactivity, image recognition, advertising, and marketing.

Element AI makes a case that its jumbo early fundraising round sets a record as “the largest Series A funding round for an artificial intelligence company in history.”

But, as with all records, it depends on your definitions. Business data firm CB Insights says the $200 million Series A financing round in June 2016 for Menlo Park, CA-based self-driving car startup Zoox occupies the top spot. Autonomous cars depend on artificial intelligence for the navigation systems they use to stay on course and avoid crashing into things. Other mega-Series A’s for AI-related companies include the $154 million reaped by health data AI and analytics company iCarbonX in April 2016, and the $100 million that Chinese company Cloudminds scored to develop its Web-based “brain” for intelligent robots, CB Insights says.

For both Zoox and iCarbonX, their big early rounds were said to peg company valuations at $1 billion.

Element AI’s CEO Gagné declined to disclose the valuation set for the startup by its huge fundraising round, or its current fundraising total.

“Right now, we’re not disclosing the total amount raised although the $102 million makes up the vast majority of the total raise,” Gagné says.

Asked why AI companies would need to raise whopping amounts in their early days, Romulus Capital’s Gupta told Xconomy: “They don’t need $100 million, but one might be tempted to think ‘I can raise it so why not?’ AI companies do need a fair bit of capital as it takes a long time to incubate research and then make it commercially viable, especially when the use cases aren’t immediately obvious.”

Etzioni says: “It really depends on what you’re trying to build and whether you’re planning to build it from the ground up or need to acquire talent and IP. If there are hardware costs—whether it’s chips or robotics—that’s another driver for needing more capital.”

According to a recent CB Insights report, AI companies raised more than $4.8 billion in 698 funding deals disclosed in 2016. By March 23, 2017, before the close of the first quarter, AI startups raised $1.7 billion in 245 deals. That reflects significant growth since 2012, when companies in the sector raised $559 million in 150 deals.

Element AI’s Gagné says the startup’s profit potential makes it a reasonable bet for the investors who have advanced so much money at such an early stage.

“Our platform and business model offers a lot of monetization opportunities,” Gagné told Xconomy. “Either through licensing our technology or consulting, we are creating value and will take in a position where it makes sense for all parties involved.”

Gagné added: “We expect to do 50 projects in the next six to 12 months and currently have revenue in the millions.”

Asked how Element AI charges its clients for helping them solve problems, Gagné says, “it really depends on the situation, sometimes we charge for consulting, sometimes for licenses.”

Element AI says it worked with noted Montreal A.I. research center MILA to craft “a unique, non-exploitative model of academic cooperation” that they have now replicated to many other institutes.

“It’s a very collaborative model where we have Research Labs professors collaborate on a weekly basis in brainstorming/science curation sessions where we provide unique challenges for them to solve,” Gagné told Xconomy. “The interesting thing about it is that they get to collaborate with world-class experts in many different fields during these sessions, something they would never have access to at their lab or conference. The results are very exciting, they are producing more research papers and we are transferring a lot of technology in the commercial applications.”

Gagné declined to elaborate on the terms under which academics help Element AI to work on its projects for clients, or for itself. That leaves open whether the academics, or their universities, receive financial benefits such as consulting fees, shared revenue, and intellectual property rights.

“The work we do on the research front is typically done in an open innovation way,” Gagné says. “That’s all I can discuss at this moment.”

One thing is for sure—there will be more AI experts working for the company. With its new cache of capital, the startup plans to expand globally and hire another 250 employees in the next six to 12 months, Gagné says.

Does the company plan to recruit and/or accept job applications from engineers outside Canada, such as from Silicon Valley?

“Yes absolutely, we have been doing so already as we now have at least someone coming from every continent working at Element AI,’’ Gagné says.

Xconomy editors Jeff Engel, Benjamin Romano, and Angela Shah contributed to this report.

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