Canada has made a commitment for many years to the study of AI at universities across the county, and today robust business incubation programs supported by Canada’s state and regional governments work to transform research into viable businesses. This AI ecosystem has produced breakthrough research and is attracting top talent and investment by venture capital. Here is a look at a selection of Montreal- and Toronto-based AI startups.
TandemLaunch, Technology Transfer Acceleration
TandemLaunch is a Montreal-based technology transfer acceleration company, founded in 2010, that works with academic researchers to commercialize their technological developments. CEO and General Partner Helge Seetzen was the founder and directs the company’s strategy and operations. TandemLaunch has raised $29.5 million since its founding, according to CrunchBase. The firm has spun out more than 20 companies and has been recognized for supporting women founders.
Seetzen was a successful entrepreneur who co-founded Sunnybrook Technologies and later BrightSide Technologies to commercialize display research developed at the University of British Columbia. BrightSide was sold to Dolby Laboratories for $28 million in 2007.
TandemLaunch provides startups with office space, access to IT infrastructure, shared labs for electronics, mechanical or chemical prototyping, mentoring, hands-on operational support and financing.
Asked by AI Trends to comment, CEO Seetzen said, “TandemLaunch has a long history of building leading AI companies based on technologies from international universities. Example successes include LandR – the world’s largest music production platform – and SportlogiQ which offers AI-driven game analytics for sports. Many younger TandemLaunch companies are at the brink of launching game-changing products onto the market such as Aerial’s AI for motion sensing from Wi-Fi signals which will be released in several countries as a home security solution later this year. With hundreds of AI developers across our portfolio of 20+ companies, TandemLaunch is well positioned to capitalize on AI opportunities of all stripes.”
Other companies in the TandemLaunch portfolio include: Kalepso, focused on blockchain and machine learning; Ora, offering nanotechnology for high-fidelity audio; Wavelite, aiming to increase the lifetime of wireless sensors used in IoT operations; Deeplite, providing an AI-driven optimizer to make deep neural networks faster; Soundskrit, changing how sound is measured using a bio-inspired design; and C2RO, offering a robotic SaaS platform to augment perception and collaboration capabilities of robots.
Learn more at TandemLaunch.
BenchSci for Biomedical Researchers
BenchSci offers an AI-powered search engine for biomedical researchers. Founded in 2015 in Toronto, the company recently raised $8 million in a series A round of funding led by iNovia Capital, with participation including Google’s recently-announced Gradient Ventures.
BenchSci uses machine learning to translate both closed-and open-access data into recommendations for specific experiments planned by researchers. The offering aims to speed up studies to help biomedical professionals find reliable antibodies and reduce resource waste.
“Without the use of AI, basic biomedical research is not only challenging, but drug discovery takes much longer and is more expensive,” BenchSci cofounder and CEO Liran Belenzon stated in an account in VentureBeat. “We are applying and developing a number of advanced data science, bioinformatics and machine learning algorithms to solve this problem and accelerate scientific discovery by ending reagent failure.” (A reagent is a substance used to detect or measure a component based on its chemical or biological activity.)
In July 2017, Google announced its new venture fund aimed at early-stage AI startups. In the year since, Gradient Ventures has invested in nine startups including BenchSci, the fund’s first known health tech investment and first outside the US.
“Machine learning is transforming biomedical research,” stated Gradient Ventures founding partner Ankit Jain. “BenchSci’s technology provides a unique value proposition for this market, enabling academic researchers to spend less time searching for antibodies and more time working on their experiments.”
BenchSci told VentureBeat is tripled its headcount last year and plans to add 16 new hires throughout 2018.
Learn more at BenchSci.
Imagia to Personalize Healthcare Solutions
Imagia is an AI healthcare company that fosters collaborative research to accelerate accessible, personalized healthcare.
Founded in 2015 in Montreal, the company in November 2017 acquired Cadens Medical Imaging for an undisclosed amount, to accelerate development of its biomarker discovery processes. Founded in 2008, Cadens develops and markets medical imaging software products designed for oncology, the study of tumors.
“This strategic transaction will significantly accelerate Imagia’s mission of delivering AI-driven accessible personalized healthcare solutions. Augmenting Imagia’s deep learning expertise with Cadens’ capabilities in clinical AI and imaging was extremely compelling, to ensure our path from validation to commercialization,” stated Imagia CEO Frederic Francis in a press release. “This is particularly true for our initial focus on developing oncology biomarkers that can improve cancer care by predicting a patient’s disease progression and treatment response.”
Imagia co-founder and CTO Florent Chandelier said “Our combined team will build upon the long-term outlook of clinical research together with healthcare partnerships, and the energy and focus of a technology startup with privileged access to deep learning expertise and academic research from Yoshua Bengio’s MILA lab. We are now uniquely positioned to deliver AI-driven solutions across the healthcare ecosystem.”
In prepared remarks, Imagia board chair Jean-Francois Pariseau stated, “Imaging evolved considerably in the past decade in terms of sequence acquisition as well as image quality. We believe AI enables the creation of next generation diagnostics that will also allow personalization of care. The acquisition of Cadens is an important step in building the Imagia platform and supports our strategy of investing in ground breaking companies with the potential to become world leaders in their field.”
Learn more at Imagia.
Ross Intelligence: Where AI Meets Legal Research
Ross Intelligence is where AI meets legal research. The firm was founded in 2015 by Andrew Arruda, Jimoh Ovbiagele and Pargies Dall ‘Oglio, machine learning researchers from the University of Toronto. Ross, headquartered in San Francisco, in October 2017 announced an $8.7 million Series A investment round led by iNovia Capital, seeing an opportunity to compete with the legal research firms LexisNexis and Thomson Reuters.
The platform helps legal teams sort through case law to find details relevant to new cases. Using standard keyword search, the process takes days or weeks. With machine learning, Ross aims to augment the keyword search, speed up the process and improve the relevancy of terms found.
“Bluehill [Research] benchmarks Lexis’s tech and they are finding 30 percent more relevant info with Ross in less time,” stated Andrew Arruda, co-founder and CEO of Ross, in an interview with TechCrunch.
Ross uses a combination of off-the-shelf and proprietary deep learning algorithms for its AI stack. The firm is using IBM Watson for some of its natural language processing as well. To build training data, Ross is working with 20 law firms to simulate workflow example and test results.
Ross has raised a total of $13.1 million in four rounds of financing, according to Crunchbase.
The firm recently hired Scott Sperling, former head of sales at WeWork, as VP of sales. In January, Ross announced its new EVA product, a brief analyzer with some of the power of the commercial version. Ross is giving it away for free to seed the market. The tool can check the recent history related to cited cases and determine if they are still good law, in a manner similar to that of LexisNexis Shepard’s and Thomson Reuters KeyCite, according to an account in LawSites.
EVA’s coverage of cases includes all US federal and state courts, across all practice areas. “With EVA, we want to provide a small taste of Ross in a practical application, which is why we are releasing it completely free,” Arruda told LawSites. “We’re deploying a completely new way to doing research with AI at its core. And because it is based on machine learning, it gets smarter every day.”
For more information, go to Ross Intelligence.
Phenomic AI Uses Deep Learning to Assist Drug Discovery
Phenomic AI is developing deep learning solutions to accelerate drug discovery. The company was founded in Toronto in June 2017 by Oren Kraus, from the University of Toronto, and Sam Cooper, a graduate of the Institute of Cancer Research in London. The aim is to use machine learning algorithms to help scientists studying image screenings to learn which cells are resistant to chemotherapy, thus fighting the recurrence of cancer in many patients. The AI enables the software to comb through thousands of cell culture images to identify those responsible for being chemo-resistant.
“My PhD at U of T was looking at developing deep-learning techniques to automate the process of analyzing images of cells, so I wanted to create a company looking at this issue,” stated Kraus in an account in StartUp Here Toronto. “There are key underlying mechanisms that allow cancer cells to survive in the first place. If we can target those underlying mechanisms that prevent cancer coming back in entire groups of patients, that’s what we’re going for.”
Cooper is working towards his PhD with the department of Computational Medicine at Imperial College, London, and also with the Dynamical Cell Systems team at the Institute of Cancer Research. His research focuses on developing deep and reinforcement learning solutions for pharmaceutical research.
An early research partner of Phenomic AI is the Toronto Hospital for Sick Children, in a project to study a hereditary childhood disease.
The company has raised $1.5 million in two funding rounds, according to Crunchbase.
Learn more at Phenomic AI.
Erudite.ai Aims at Peer Tutoring
Erudite.ai is marketing ERI, a product that aims to connect a student who needs help on a subject with a peer who has shown expertise in the same subject. The company was founded in 2016 in Montreal and has raised $1.1 million to date, according to Crunchbase. The firm uses an AI system to analyze the content of conversations and specific issues the student faces. From that, it generates personalized responses for the peer-tutor. ERI is offered free to students and schools.
Erudite.ai is competing for an IBM Watson XPrize for Artificial Intelligence, being one of three top 10 teams announced in December, from 150 entrants competing for $5 million in prize money. President and founder Patrick Poirier was quoted in The Financial Post on the market opportunity, “Tutoring is very efficient at helping people improve their grades. It’s a US $56 billion market. But at $40 an hour, it’s very expensive.” Erudite.ai is giving away its product, for now. The plan is to go live in September and host 200,000 students by year-end. By mid-2019, the company plans to sell a version of the platform to commercial tutoring firms, to help them speed teaching time and reduce costs.
The company hopes to extend beyond algebra to geometry, then the sciences, in two years. “The AI will continue to improve,” states Poirier. “In five years, I hope we will be helping 50 million people.”
Learn more at Erudite.ai.
Keatext Comprehends Customer Communication Text
Keatext’s AI platform interprets customers’ written feedback across various channels to highlight recommendations aimed at improving the customer experience. The firm’s product is said to enable organizations to audit customer satisfaction, identify new trends, and keep track of the impact of actions or events affecting the clients. Keatext’s technology aims to mimic human comprehension of text to deliver reports to help managers make decisions.
The company was founded in 2010 in Montreal by Narjes Boufaden, first as a professional services company. From working with clients, the founder identified a gap in the text analytics industry she felt the firm could address. In 2014, Keatext began offering a SaaS product offering.
Boufaden holds an engineering degree in computer science and a PhD in natural language processing, earned with the supervision of Yoshua Bengio and Guy Lapalme. Her expertise is in developing algorithms to analyze human conversations. She has published many articles on NLP, machine learning, and text mining from conversational texts.
Keatext in April announced a new round of funding, adding CA$1.72 million to support commercial expansion, bringing the company’s funding total to CA$3.32 million since launching its platform two years ago. “This funding will help us gain visibility on a wider scale as well as to consolidate our technological edge,” stated Boufaden in a press release. “Internet and intranet communication allows organizations to hold ongoing conversations with the people they serve. This gives them access to an enormous amount of potentially valuable information. Natural language understanding and deep learning are the keys to tapping into this information and revealing how to better serve their audiences.”
Learn more at Keatext.
Dataperformers in Applied AI Research
Founded in 2013 in Montreal, Dataperformers is an applied research company that works on advanced AI technologies. The company has attracted top AI researchers and engineers to work on Deep Learning models to enable E-commerce and FinTech business uses.
Calling Dataperformers “science-as-a-service,” co-founder and CEO Mehdi Merai stated, “We are a company that solves problems through applied research work in artificial intelligence,” in an article in the Montreal Gazette. Among the first clients is Desjardins Group, an association of credit unions using the service to analyze large data volumes, hoping to discover hidden patterns and trends.
Dataperformers is also working on a search engine for video called SpecterNet, that combines use of AI and computer vision to find specific content. Companies could use the search engine to identify videos where their products appear, then market the product to the video’s audience. The company is using reinforcement learning to help the video search AI to learn on its own.
Learn more at Dataperformers.
Botler.ai Bot Helps Determine Sexual Harassment
Botler.ai was founded in January 2018 by Ritika Dutt, COO, and Amir Moraveg, CEO, as a service to help victims of sexual harassment determine whether they have been violated. The bot was created following a harassment experienced by cofounder Dutt.
She was unsure how to react after the experience, but once she researched the legal code, she gained confidence. “It wasn’t just me making things up in my head. There was a legal basis for the things I was feeling, and I was justified in feeling uncomfortable,” she stated in an account in VentureBeat.
The bot uses natural language processing to determine whether an incident could be classified as sexual harassment. The bot learned from 300,000 court cases in Canada and the US, drawing on testimony from court filings, since testimony aligns most closely with conversational tone. The bot can generate an incident report.
This is Botler.ai’s second product, following a bot made last year to help people navigate the Canadian immigration system.
Yoshua Bengio of MILA is an advisor to the startup.
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