CanadianAI: Calgary, Waterloo, Toronto, Montréal. A cross-country week of AI raises, two Canadian flags at CVPR, and a national strategy that finally landed.
Also some good data on AI Adoption, and Canadian public's sentiment on AI.
Good morning! Welcome to the Canadian AI Newsletter, a weekly rundown for founders, operators and investors.
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I am Raif Barbaros, Partner at Mistral Venture Partners. Views are my own.
The wait is over. After slipping past three self-imposed deadlines, Canada’s national AI strategy finally landed on Wednesday, and it is big, expensive, and aimed squarely at one thing: getting Canadians to use AI. I break down below what is actually new money versus re-announced money, and why an adoption-first strategy may be pointed at the wrong target. Around it, a lively week of out-of-Toronto deals from Calgary, Kitchener-Waterloo, and Montréal, two Canadian flags at CVPR in Denver, and fresh data from the Bank of Canada and Angus Reid that should give the adoption thesis pause. Let’s get into it.
💰 Deals & Milestones
Pricepoint (Montréal) raised a US$4.8M seed to put AI in charge of hotel room pricing.
An all-Québec syndicate: Brightspark Ventures led, with Boreal Ventures and AQC Capital. Brightspark’s Sophie Forest and Boreal’s JD Saint-Martin take board seats, and the money roughly doubles a 35-person team.
The product is autonomous revenue management, software that sets and resets room rates in real time the way airlines or larger hotel chains have for decades. Pricepoint makes it available for the individual franchisees.
I’ve known Mateusz Sznir, founder and CEO, for a few years. He comes from the industry and is super passionate about the problem he’s solving. A true operator and nice human.
SensorUp (Calgary) closed a growth round led by Pender Ventures to scale agentic AI for heavy industry.
Climate Investment and Evok Innovations joined, alongside Occidental as both strategic investor and customer. Pender’s Cheri Corbett joins the board. No dollar figure was disclosed, which is its own tell, but the platform is already in production with five member companies of the Oil and Gas Climate Initiative.
Not chatbots, but software agents running emissions monitoring and field operations for the energy sector. A Calgary company selling AI into oil and gas.
Scispot (Kitchener-Waterloo) raised a US$8M Series A to build the operating layer for AI-run life science labs.
Washington’s Avenue Growth Partners led, with Seattle’s Breakwater Ventures returning, taking total funding to about US$10M. Avenue’s Brian Goldsmith joins the board.
Scispot calls it the “self-driving lab”: software that wires together instruments, data, and AI so life-sciences experiments run with less human babysitting. Picks and shovels for the biotech-AI boom, and another Waterloo-corridor company worth watching.
Mecka AI (Toronto talent, New York address) disclosed US$60M to build the data layer for humanoid robots.
Framework Ventures led, with Menlo Ventures, SV Angel, and Kindred Ventures alongside. The detail that earns it a place here: three of four founders are Canadian and 40 of 45 staff sit in Toronto, even as the company is headquartered in New York. Framework’s Vance Spencer called it the fastest-growing revenue company the firm has ever backed.
A caveat I’ll flag plainly: this is a disclosure of rounds that closed earlier, a US$25M Series A last November plus a follow-on, not a fresh raise this week. I include it because the talent base is unmistakably Canadian, but the cap table and the HQ are not 😔
🏢 Large Companies
Cohere (Toronto) open-sourced co/plot, a data-visualization tool built inside its research labs and described in a post by Cohere’s Thomas Euyang. (Disclosure: Cohere is a Mistral Venture Partners portfolio company.)
🔬 Research
CVPR, the year’s biggest computer-vision conference, ran June 3 to 7 in Denver, and Canada planted two flags. Both are collaborations with Apple, with the Canadian angle in the academic authors.
Mila and Université de Montréal presented SFI-Bench, a benchmark that asks whether multimodal models understand what objects are for, not just where they are.
Built from more than 1,700 questions over egocentric indoor video, it tests “spatial-functional intelligence,” the difference between seeing a kettle and knowing you boil water in it. Senior author Aishwarya Agrawal is a Canada CIFAR AI Chair and Mila core member; Le Zhang is the lead author.
Why it matters: today’s vision-language models are good at naming and locating, and still clumsy at function and affordance. If you want robots and agents that act in the world, this is the gap that has to close, and a Canadian lab is building the ruler to measure it.
The University of Toronto presented Velox, a method for learning compact representations of moving 3D scenes, four dimensions counting time.
PhD student Anagh Malik and professor David Lindell compress spatiotemporal point clouds into “dynamic tokens” usable for video-to-4D generation, 3D tracking, and even cloth simulation.
It is the unglamorous foundation under flashier generative-video demos. Better 4D representations feed straight into robotics perception and world models, the physical-AI thread Raquel Urtasun keeps pounding the table about.
🏛️ Policy
Canada finally has a national AI strategy. On Wednesday, Mark Carney and AI Minister Evan Solomon launched “AI for All” at Toronto General Hospital, closing out a saga that blew through every previous deadline. The full strategy is sprawling. Two things are worth your time: where the money actually is, and what the strategy is actually trying to do.
Follow the money, and separate the new from the recycled. The Globe pegged it at “more than $2.3-billion,” and Carney framed the package as building on roughly $2B already committed. Both are true, and neither is the whole picture. Here is the honest split.
Genuinely new, strategy-attached money, roughly $2.86B:
A $500M Canadian Tech Growth Fund that will take equity stakes in scaling Canadian AI firms. This is the real shift, Ottawa moving from writing grants to taking ownership.
A $200M AI Missions program, first mission health.
$50M to expand the Canadian AI Safety Institute, and $130M to commercialize research out of Mila, Vector, and Amii.
Re-announced or topped-up money doing a lot of the headline work:
$500M for BDC’s LIFT facility, which BDC already announced back on April 24.
A $500M top-up to the existing Regional AI Initiative, and a $700M top-up to the existing Compute Access Fund, the one that has already cut $66M in cheques.
Budget 2025’s $1.75B and April’s $25B sovereign wealth fund sit in the backdrop as the capital backstop.
Add up the named line items and you reach roughly $8.5B. The genuinely new, strategy-specific commitment is closer to $2.86B. The “$2.3B in new spending” headline holds up only if you count the Tech Growth Fund, Missions, CAISI, and commercialization money as new, and treat the top-ups as fresh. A fair chunk of the rest, we have reported before.
Now the bigger point: this is an adoption strategy. Strip away the funding tables and the organizing goal is to get Canadians and Canadian businesses using AI. The centerpiece target is lifting business AI adoption from just over 12% to 60% by 2034. The gap is real: barely 12% of Canadian firms used AI to make goods or services over the past year, and SMEs sit around 8%, versus 26% in Germany and into the 40s in the Nordics.
My take. Adoption is good. A country that does not use AI never gets the productivity dividend, and the Bank of Canada data below shows how far we have to go. But adoption is not where power and wealth are created. Power and wealth come from building the AI and capturing the value, owning the models, the companies, and the IP, rather than renting someone else’s. There is some value-capture logic buried in here: the Tech Growth Fund taking equity, the money to commercialize institute research. That is the right instinct, but mostly implicit. What I do not see is firm industrial policy, the kind the US and China run without apology, that bends procurement, standards, and market access to favour Canadian companies. We are funding Canadians to use AI built elsewhere and hoping a few champions emerge on their own. The countries we are competing with are writing the rules so their champions win. Not an area we need to be kind in ;)
📊 Data
The Bank of Canada put a number on the adoption gap the strategy is chasing. A new staff paper by Chanya Chawla and Crystal Arnburg, drawing on the Bank’s December 2025 Business Leaders’ Pulse, finds AI use among business leaders is widespread personally but still limited in actual production.
The forward look is sobering for the “AI means jobs” framing: firms expect AI to lift capital spending, but to have a modest net negative effect on employment over the next three years.
Angus Reid ran two surveys that, read side by side, should temper the adoption optimism.
On regulation, Canadians want guardrails: 68% say government should heavily regulate AI even if that slows things down, 74% doubt any government can keep pace, and 68% would oppose a large AI data centre near their home. President Shachi Kurl’s read is that there is a wide gap between where the government is going and where Canadians are.
On work, the verdict is a shrug. Among Canadians who use AI on the job, 49% say it has had no impact on their productivity and only 29% say it improved the quality of their work. Just 31% have an employer with an actual AI policy. And the tools people reach for are American: Gemini at 48% and ChatGPT at 47% lead, while Claude sits at 9%. A strategy built on adoption is, in practice, a strategy built on Canadians using other countries’ models.
📰 In brief
Inovia Capital (Montréal) reported its third growth fund has reached US$365M of a US$450M target. AI-native startups took 40% of Canadian software deal value in 2025. The capital is flowing.
S&P Global partnered with Cohere to put its financial data inside Cohere’s enterprise platform, North, for on-premise agentic workflows at financial institutions. (Disclosure: Cohere is a Mistral Venture Partners portfolio company.)
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— Raif