The Lean Startup Mentality for Canada’s AI Scale-Ups

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What does CANN Forecast do? 

At CANN Forecast, we leverage artificial intelligence (AI) to help municipalities and private companies better manage their water and their infrastructure. We have two products, InteliSwim, which predicts water quality in lakes and rivers, and InteliPipes, which identifies which water mains are most likely to break in the short-term so cities can replace them proactively. 

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What has been your experience in scaling your company? 

One of the main challenges we have is that because we pride ourselves in producing high-quality results, as we scale and get more customers, the team that has been trained to generate such high-quality output finds it difficult to scale the same level of quality as fast as the demand comes. It is a blessing for us and a good problem to have but eventually, we decided that if we ever have to compromise on quality, we will scale slower. Now, we are in a situation where we have to tell some of the people that are interested in working with us, “Can you wait until March before we start the project so we can make sure to give you the same quality all of our customers have received so far?”  

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What key pressure points do Canadian SMEs entering this scale-up phase face? 

We are doing a lot of things right in Canada, at least in Quebec. The whole ecosystem for mentorship for startups is huge and very active. We have MentorConnect, which was founded at MIT and is taking over in Canada. It consists of a bunch of very experienced entrepreneurs and people from the public sector who are willing to give a few hours in a month to young entrepreneurs to teach them how to do business. We have Montréal Inc., which is for Montreal but is now starting to also get to some of the cities close to Montreal. Entrepreneurs can apply and once they are accepted, they get into cohorts where they get training and feedback. We have a lot of accelerators throughout Quebec, so this is really nice for startups that want to scale.  

“We need better access to human resources specifically in AI.” 

At the same time, we need better access to human resources specifically in AI. It is becoming more and more difficult to find the right people to do the job because the best researchers are usually taken by big firms. Everybody else usually says they can do AI but do not necessarily have all the credentials to do it. 

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What supports do you think are missing in the Canadian ecosystem? 

One of the things I have come to realize that could be improved in the way we do business innovation specifically in AI, is that through certain organizations like Mitacs, the government has allowed companies and startups like us to work with academia. However, there are still two different worlds in the sense that as a startup, you have to iterate as fast as you can to bring a product to market. Once you have something that works, it is good enough to iterate and bring to market. In academia, they have to publish papers and take their time to do their literature reviews. AI companies and academia are both trying to innovate in the long run, but the incentives are different on each side. If we could come together and implement a lean startup methodology to bring R&D from academia to industry, and then to the hands of the people, that would be a game-changer. 

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How can we ensure that Canadian tech companies can commercialize and thrive? 

In Canada, we are very good at research and development. This gets to the point that I brought up earlier about how we should bring a lean startup way of thinking to the collaborations between academia and industry. We have to agree on a definition of what is good enough so that we can push that to market as soon as possible. It will be amazing if we keep publishing and keep being known for our research, but at some point, all of this great research should be translated into innovative products that will make us shine by what we are developing for the end customer. 

“We should bring a lean startup way of thinking to the collaborations between academia and industry.” 

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What advice would you give other founders and entrepreneurs?  

The advice that saved us was to stay as close as possible to our customers. Even from the beginning, we have been co-developing all of our solutions with our customers. Before we start a new project, we email municipalities and tell them about the idea that we have and ask whether they would be interested in being part of it. They do not need to pay a lot of money if it is at the beginning of the creation of the product, but if you can get future customers to be involved from the beginning, then at least you know that you have product-market fit. Having this is definitely the one thing that will save many startups, because they will know that they already have people that are paying for their products from the beginning. 

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What advice would you give to a company on the cusp of scaling up? 

Not compromising quality even though it means that you are going to scale slower. At the end of the day, customers talk and it is a small world. The brand reputation of being an excellent team that always does more than the customer asks for is something of value that can sustain a business for a long time. Yes, the temptation is great because you have built a product and all of a sudden people want it, and they want it more than you can give, but you should know when to postpone a project if it means that you would have been compromising quality. This is important because in the end, if your brand is strong, that is one of the most important things. 

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Who and what would you pitch about improving Canadian companies’ ability to scale up?  

I would choose government, academia, and industry. I would ask if we can get together and build a new process to bring innovation to people faster. We all want the same thing in the end. If we change some of the incentives for all of the parties involved, we may be able to develop a model that other nations will follow.