AI Salon x Flagship: Live @ Mila

Eleonore Jarry: I'm lucky to be sitting with, three great investors that are based in Montreal, actively investing in Montreal. Claude did put us on the spot that we should invest more in our local AI companies. So we're definitely all on the end for for great founders.

So come talk to us at the end. All of this conversation is really to bring light into each individual is thinking about investing in AI right now. AI is set to be probably the fastest growing and fastest changing tech cycle we've seen so far which makes it really exciting, but also very hard to navigate as an investor.

So we wanna bring some of the thoughts that maybe you won't be reading online about each investor or thinking about investing. In AI or generally? Right now. So myself, I'm Eleanor. I'm at Bright Spark Ventures. We're an early stage fund. We invest from creation all the way to Series A. Mostly rounds we lead and across all verticals.

And I'll ask all my panelists right now to briefly introduce yourself with a bit of background on yourself, quickly and the firm you're at and where you invest.

Hugues Lalancette: Alright? Very excited to be here, by the way. I'm a partner at Inovia. I joined a firm about 10 years ago, which is crazy when I think about it.

At the time we we were 10 people. It felt like a startup. We had a venture fund and we basically 10 x that across pretty much every KPI. So we're now managing about 2.5 billion US across pre-seed all the way to growth. So think of us as the kind of largest Canadian anchored VC fund that can support entrepreneurs across stages.

And yeah, it's a full circle moment. I think. I started running around the mile in and chasing people with the Hawaiian shirts. Not too far from here. Very excited for this this conversation.

Catherine: Good. First of all, really happy to be with you guys tonight. And I'm really liking this panel.

This is great because I'm the newcomer, but I've known like you guys since for 15, 20 years. So it's really good to be to be with you guys tonight. My name is Catherine. I am I I lead the seed fund at white Star Capital white Whiteside Capital. We are a global fund with with offices in Montreal, Toronto, New York, London Paris, Abu Dhabi, and Singapore.

And we really started like a global fund. Our first fund 15 years ago was a $17 million global fund, and we invested both in Europe, Asia, and North America at the same time. So truly Global fund. We we are more known as a series A, series B fund, but recently we saw we felt that there was a gap in the market.

Thankfully you and I, and then you as well are starting to fill that gap at Prese seed stage. So we decided to start a seed fund, and we'll talk about more of our thesis and so on later on. But we're most, mostly a generalist tech firm. And on myself. I I used to be, I used to work at Work Leap, previously known as at G saf as basically the number three.

There I was the chief strategy and corp dev officer. Spent 10 years there scaling the business from 50 million to 250. I had quite a journey there. But so many learnings that I wanted to bring back to the community, mostly around the fact that I think one of the reason why we were able to reach that skill was that we were global, first or third customer at work.

Leave GSO was was American. And that this is this is why I wanted to this is what I want to bring to the ecosystem. I wanna help company think global Day one and build company that can reach that scale.

Dominic Becotte: Hello everyone. My name is Dominic. I'm pleased to meet you managing partner at Amir Ventures. Amiel is a new name in the market. I've launched I've launched with Fred. Economic is happy to announce that we're closing in two weeks. We're super happy. We've been, we've been closing in two weeks for a year now.

We're really excited. This is a we're, but this is a real thing. The funds

Catherine Ouellet Dupuis: we're raising too, by the way, where we feel the pain. Yeah. It's a humbling

Eleonore Jarry: experience that brings the empathy of, being in the market, raising money.

Dominic Becotte: It is a it is a very challenging experience, but it is it is, to me the best the best job you can do.

We're basically based in Montreal with the Pan-Canadian ambitions investing in early stage companies late seed small series A. But we we like to say that we or or a goal is really to provide, of course, capital but also to provide expertise with a a fantastic network of mentor investors and ourselves providing expertise to entrepreneurs and support the best companies in Canada.

Eleonore Jarry: Great. Let's dive in a little bit more into investment thesis, especially as it relates to ai. Innovia has been around for almost two decades now. You've been with the firm for 10 years. You if invested in true multiple cycles. How was your thinking in investing in AI change over the past two, three years?

There's stuff that you invested in the past two, three years that you wouldn't invest in today, or vice versa, stuff you would've not done, but that you're now considering and in the context that, you've probably all read articles that, AI is changing the basic playbook and some of it is true.

Some of the, some of it is not. So curious to hear your thoughts about that.

Hugues Lalancette: No, it is a bit of a psychotic time. I was chatting with at Bud Press, which we had the chance of banking earlier, so I won't steal a thunder. But it's never been I can't remember a time where I, we actually don't know what our next investment's gonna look like in six months, which is like both scary and exciting at the same time.

I would say if you take a three year timeframe we spend a lot of time at the LLM layer. We're lately spending a lot more time at the application layer and at the infrastructure layer. And so for example, we just co-ed the cohere 600 million round. We think that LLM layer is harder just because of the scale of compute and capital that, that you need to build these businesses.

If you're not a hyperscaler, harder as an investor but yeah, we look, we we are very active in the market. We think it's, it is a transformative wave and we've been, investing across that application stack. So lately we doubled down on spell book, which is building Legal Tech out of St.

John. There are Series B us coed there with Csla, and it's in St. John. I can't wrap my head around that. It's just a, fantastic community out there. Also Flair we recently invested in cybersecurity with the White Star, our friend at White Star. The whole idea there being that there are so many new attack vectors with ai, that cybersecurity market itself is just like growing by an order of magnitude.

And same for Bud Press, that's more in the infrastructure layer. So we've really been active up and down the stack. I don't think it's a market you can play defense in. It's a bit psychotic that way. But the stakes are higher, so we can talk a little bit about that.

Eleonore Jarry: Thanks Agan, Dom and Katherine, you have the luxury to be starting a fund now, writing your thesis.

How have you incorporated AI or not in drafting that thesis for it to be, proactive, offensive, a bit contrarian, but still that will, stand the test of time and evolve well with the firm?

Catherine: I'm I'm building a new fund, but I have the luxury of being part of the White Star family. So it's something that I'm trying to to to get the insights from the team that invested, the teams I invested before me.

But first of all, what a time to be alive and to be working in tech. It's amazing to be working in tech. On the investment side generally white side, we try, we tend to be a bit, we try to be as pragmatic as possible. For example, there are a lot of AI company that have quick, early growth actually, like impressive growth.

But through analysis White Star we we realized that a lot of these companies had much higher churn than traditional SaaS. Like traditional SaaS would have a four, 5% churn, but for a lot of these like AI native app, you'd have churn even around 50%. So we try to steer a bit more coal headed and be pragmatic about these investment and get back to the, even if it's ai, it's exciting.

Everybody wants to get in. What are the, going back to the fundamentals the team or like, how's the team? What are they, what's the problem they're working on and what's the competitive mode that they're having and the product that they're building are they embedded into the customer workflow?

Are they like, are they gonna stay there? Are they sticky? Are they delivering true value to the customers? I know it these all things that, make sense on paper, but ev there's this AI wave and everybody's excited about investment and it's hard for us not to jump into this, but we try to be a bit more pragmatic about about this.

About ai we do like vertical SaaS a lot at at White Star. So not necessarily a pure AI play, but companies that would leverage ai, for example but Flare is one. I love cybersecurity. Actually Al former CFO at W Work, Kleef, GF is there. And I once was the head of cybersecurity at White Stars work Leap.

I love that space. But for example, flare is leveraging, it's not an AI native app, but is leveraging AI to help customers prioritize like the issues to tackle. But another example is Venture. One of our other investment. They're like, they're leveraging through a partnership with in Nvidia a lot of data that they accumulated through their like a thousand thousands of robots.

And now they're able to have a robotic arm that automatically determines it flow. So they're like, it's very exciting, the opportunity. And but that's an example of vertical SaaS that that we like to invest in. But we do also do AI play you talk about foundational model, I think.

It's true that at Pres precedes siege stage right now, it's hard to invest in foundational model that that are there to impact productivity. I think we're a bit late in the game. You did good with Cohere, but we're, it's a bit late for us, but we're ATS precedes seed. Not really in Quebec, but in the US 'cause we're, my fund is a North America fund.

We invest both in Canada and the us and in the US we're starting to look at industry specific foundational model. So these are things that, that we're looking at, but still trying to be pragmatic about it and is this something that is is that our customer customer flock from one to the other or it's really something that is embedded in the customer workflow and that will that will be there for the long term and durable.

Is there something you didn't do at Worksheet by Catherine? Or you did it's also business? Yeah, I it's funny, like I, I see it like a vc, like it's surprising, but we're building a business ourselves. So that's really what I like about, about us. I know that may not look like that from the outside.

Yeah, no we're trying to build a business. Yeah. There's a

Eleonore Jarry: lot of background work that founders don't necessarily get to see, and sometimes it's better this way. Dumb, I know data is very central also in your own investment thesis and industry specific knowledge. Yeah. Same question. How do you incorporate thinking about investing in AI in a brand new admiral fund?

Dominic Becotte: Yeah. Thanks for the question we're as Catherine said, we're cautious, cautiously optimistic. We're prudent, but really excited at the same time, at Al, we're we're investing, we're, we have a niche investing thesis. We're investing in enterprise ai. We're looking at the way AI can truly transform enterprises from a productivity, sustainability, profitability standpoint.

We're seeing AI as really an enabler today, not as the main driver for differentiation. I think we all agree that AI has become democratic really rapidly. Everybody has access to good ai. Even my 6-year-old beliefs that Chad GT is smarter than me, and she's probably right.

She's right. So it's become a commodity. So what do you do from a business point of view? You wanna build a startup? In that case, what do you do? So data to us. Is the real driver. You have access. Can you show as a startup company or entrepreneur, you have access, privilege, access to data sets.

Is it unique? Is it your main innovation? And this is what we want to see as in investors the way you get access to privileged corporate data sets. Are you doing it in a, with the highest security standards in the corporate world? You have no choice. So this is really what we what we want to look at.

And this is, in fact, this is one of the main reasons we invested in Maxa first last year, then maquette this year. And this is really the point, getting access and exploiting valuable data sets. So we really believe that the strongest AI companies will be the companies building this, the those platforms or this infrastructure to get access to really valuable data and building value from it.

Hugues Lalancette: I was gonna say, I, how we always run out of time for these, but it's good like this. Okay.

Eleonore Jarry: Another question, and yes, I see the time flying. Twofold question. There was a great report issued by Carta today was clearly showing that AI companies are taking the lion's share of the VC funding going to companies.

And it feels like the market is your discussion. I think polarized is a good way of whether you're a AI company or you're not, and your fundraising experience is very different depending on which category you fall. So curious to hear what are you seeing on the ground in the VC market right now and looking at a crowd, what advice would you give to someone who's thinking about coming to market to raise capital for a company, especially if, for example, it is a company sued out of research or a more deep tech venture.

Hugues Lalancette: No, look it's crazy. I think the good news is that all these problems are investor problems. I think it's never been a better time to build as an entrepreneur, you just don't need to worry about it too much. You'll you can raise if you want to capital is plentiful.

But I would say maybe for the folks in this room, what's very exciting as a trend for us is seeing AI blurred the land the lines between research and startups. You, we, 10 years, 10, 15 years ago, there, there used to be this belief that researcher can build the company and, f 500 billion later, and a few open the eyes and then tropics.

I think that assumption's been thrown in the trash. So it's a very interesting time. I would say that the speed at which things are moving is probably the thing as an entrepreneur that, that is keeping you on the edge. But look if you're gonna build I think the options are also not to raise, right?

There's also the pad of bootstrapping, leveraging all the tools out there. And so what we're seeing is really. This new cohort of companies that are achieving unprecedented growth. And so I would just keep in mind that there's like a vector in your vision and your velocity that is being resetted by these kind of pure play AI companies.

And that's really the competition. But again, if you look at sources of capital and just the type of market opportunities, we went from a world where VCs invested in technology tools to actually addressing market that are as large as the economy itself. And that to me is is very exciting.

So

Eleonore Jarry: would you say that the bar is higher, but the opportunity is also bigger?

Hugues Lalancette: Yeah. I think I was coming here on the, in the, in, in the taxi and the you look at companies like Lovable out of Europe, right? And you look at Cursor and others, right? They're hitting 1 billion in revenue in two, three years. And so I do think the bar is higher, but in a crazy way that is positive for entrepreneur in that the ceiling has just been lifted, right?

We're lucky to have three $10 billion plus companies in the portfolio. And that's, I think, a new kind of ceiling for Canadian entrepreneurs to reach. And when we look at our portfolio construction, we don't think of a billion dollar as the end point.

Eleonore Jarry: Catchin dumb anything to add on market read and advice for founders?

Catherine: Yeah I am I am not as optimistic as not that I am, I'm definitively super optimistic on the medium and short term and long term. But I seeing what is happening in the US and White Star, were a global fund. So we were day, like day, days and night we're working with US investor Amer and European investors and also talking to enterprise customers in the US and so on.

And we're starting to see signs of, for example, large US enterprise, not being, like, not being sure on all of the AI investments that were made and what are they getting out of this. So questioning whether or not they should start cutting tools and as part of their stack and so on.

But for sure everything is I said it at the beginning of the, that podcast what a time to be alive. But it might take time before we can deliver through value to our customers. So I'm personally expecting some correction, like always like upward trend, but some corrections in the future.

So the reason why I'm saying this is I think we, we have to remind ourselves that valuation and fundraising is not the goal. Like the goal is to deliver value for your customers and build a great product. And sometime too much cash or a too big valuation can become a problem in the long term.

We've seen it at Work Leap like one year we're like, oh my God, we're hiring a hundred people. And then we became so inefficient because like it was too fast. And then oh my God. And and then like we realize, okay, we gotta take a bit of a step back and then like maybe regroup and rethink how we gonna tackle this.

So when you raise a lot, a large round at a high valuation, like if that's the right thing to do, amazing with do it. But you have what are we gonna, what are you gonna deliver with that value? And if the music stops, when it'll be time for you to fundraise, will you be proud of what you have done with that money?

So I think that's an advice that I would, I would give to founder and if fundraising large amount. And that's your pat. And that's what you need to win the market. And in 18 months when you have to fundraise again yeah. Like you'll be in a great position then do it.

But it's some, it's something to keep in mind definitively.

Dominic Becotte: Yeah. I would just say that one interesting point that we that we're saying today is that that I was in the market 20 years ago and 20 years ago funding a company with a seed brown. The goal was to build that company up to 40, 50 employees.

And today, boy, seed round company is gonna need 15, 20 employees at the end of the day. So capital is much more efficient today. And this is truly interesting to me because you can do much more with capital. And this is really interesting from a, from coming from a vc, of course, it's a, I mean your money, your investment in talented entrepreneurs can do more.

So it's I think it's a, it's really one thing, but I agree with you with both of you guys but rine you talked about value, and I think that's your goal as entrepreneurs to build and to show value to your customer. In my case, we're looking at corporate clients companies showing ROI preferably with dollar signs.

It's it is the best demonstration that you have built something that is extremely valuable. This is a what Maxa has done. It's, there's a clear dollar sign demonstration. You can see the impact. So if, your job is to become the best crack dealer out there really because you're selling amazing technology to a company that could no long could no longer live without you.

And this is that it's something that is possible today in the current market. And this is something that you can build in, in, in a year or so. So again, to my point, cautiously optimistic but the excitement is is really there.

Eleonore Jarry: Yeah, I think it, if I take a little bit of like bits from everyone it is one of the most exciting time to build a company to go faster, to go bigger than ever before, but keeping the mindsets of long-term value and not chasing maybe unreasonable milestone that will not really build a company, but just, is more based on speculation or short term market needs instead of a long-term strategy will definitely, win in the long term.

Nicholas: We're doing a little something special this time. We're bringing on scale up companies that are not, at the early days needing cash just to stay alive, but have built incredible businesses and really are, the heart and soul of Montreal that we should all look up to.

With that being said, just get up here guys. We're gonna do the intro up here if it loads just lights. Nope. There we go. All right. One, two, mo I saw you somewhere.

I am like 90% sure I saw most. There we go. All right. Give it up for Vemo and Alexi.

So we're gonna start with a quick intro Of course. But I also like, as you do your intro one liner, what does your company do? And at this stage of your company, I'm assuming what keeps you up at night is not just like staying alive anymore, hopefully or going bankrupt in three hours. What keeps you up at night?

Sylvain Perron: Oh, gosh. Hi, I'm Sylva founder of bud Press. Bud Press is an AI agent platform. That means we do really good tools for people to build really good agents, deploy them. And manage them and deploy them on the cloud. Concretely what that means it means we're really good at deflecting tickets for customers.

This is most of what we do. What keeps me up at night, I guess it's not what I control at, but press as a company. But it's, where the world is going with ai, which is everything we don't really control. So yeah, I think I'm part of the dor. Categories. I think we're all a bit fucked.

Nicholas: They may not remember, but when I was doing my seed round, I asked his advice about a VC that ended up not investing in us. And I think it was a great thing ultimately. But it's great to have co-founders here that support you and it's nice to be, on the stage with you guys not that a few years later.

So I still have nightmares about the exact same things on day one, but it's kind of part, it's part of the way of life and it, you actually enjoy it at some point, being an entrepreneur. Alexi Steinman, one of the two brothers, co-founders of Maxa. Sometimes you get one brother, sometimes you get the other.

We divide and conquer. We stood up the company over five years ago. We're the number one AI analyst for enterprise finance. That means we allow finance teams and power users of systems of records or ERP systems, financial, operational systems to engage with these very complex systems, multiple of them through ai.

So if chat GT is great with language documents software code, it sucks badly with numbers and large databases. You need to give it tools. You need to beef up the reasoning and have a noded mechanism that works for enterprise. So we think we are number one in the world for that, both the harmonization technology for the underlying systems and the way that you can engage using large language models with these large databases, large systems.

So we have 50 ish people now in Montreal at Ville Marie, a small presence in Silicon Valley, and I get really fun stories when I come back from there. I may share a few tonight. And I was at a dinner the other day with Mo, another great founder in Montreal. Thank you.

Mo Wrk: Thank you. That was a fun dinner.

Hi everybody. My name is Mo. Im sorry, I just literally got off of a flight, so I'm still like a little bogged down. But so I'm the co-founder of work.com. We're not an AI company, we're an AI deployment company, and so we help organizations deploy automation and ai. We started off in the enterprise world fairly large companies and then we realized where the biggest value and where the biggest gap in the market was actually small, medium sized businesses and the benefit they could have by deploying technologies that could really make their operations a lot more efficient.

And obviously I don't wanna, I don't have to tell you about the value of AI in the workforce. We're a 6-year-old business based here in Montreal. We've been deploying automation and AI across hundreds of companies globally. And really seeing firsthand the impact that it's had on their day-to-day operations and, how they're thinking about the future of just actually technology and their own workforce, and has been really remarkable.

And, watching as, as small as like a mechanic shop with five people actually deploy ai as a voice agent for, booking appointments and answering, basic questions on the phone. So it's been really like, just interesting to see that. And then to answer your question directly, the thing that really keeps me up at night, specifically as it relates to ai, given the topic today, is it certainly feels to me like we're at a time and age where we're being forced to live with the status quo. It's a bunch of companies that own private core models that we're highly dependent on everything is in the cloud, so we're screwed because we're reliant on all of these, hundreds of millions of, and billions of dollars being deployed in data centers and whatever.

And so they, I think they it feels to me like they learned from the original experiment of the internet and America should have owned the internet, but they didn't, and they did the right thing and actually opened it up to the world. And it feels like they, they're doing that with open AI and saying instead of, democratizing it, which it should be, they've made it closed.

And now you have this battle of ai. So I love your question about data sovereignty. It's not just sovereignty, it's actually sovereignty of who owns the models and how we can expose them. So that's what the thing that I think about a lot because we're in the world of deploying AI and making it accessible.

And I think it's actually incumbent on all us of all of us, rather, to come up with a solution and not wait on government to make a regulatory framework upon which we can realize. So it's a big battle right now, I think.

Nicholas: I definitely wanna get into on that topic, and this is a discussion panel, so jump in on each other too, but I wanna go back to Alex.

So split between Montreal and SF Silicon Valley and all that, Montreal gave you talent, early adopters or tax credits and all that, what was the push that brought you out there? Was it a failure of the ecosystem? Was it, was it a growth path? Where does that come up to, grow beyond the bounds of the city?

Nicholas (2): I'll just remind people like we are sitting on the largest market in the world with incredibly effective cost base and pretty good talent. So it's it's a great place to be in the world. Like it, you shouldn't be ashamed about starting a company here. We do find people in the US that have speci specific skills.

People in Toronto. We had one opportunity in Silicon Valley. We were invited at what's called the Silicon Valley AI Hub. One kind of foundational startups that, that set up that space. We have a very prestigious employee there, so he's sitting there and our boots on the ground on location.

But it's really more a result of five years of development and hustling our way up to up the ladder in some of the larger big tech US companies. But I think it's a great base to be here. And then you have to go and opportunistically find missing talent where you go. I have a lot more to say on that, but I'll stop here.

I go to

Nicholas: S mo do you guys feel the same gravitational push and pull sometimes, like in other ecosystems and how to balance that, Montreal versus the rest of the world vibe.

Sylvain Perron: Yeah, I think we basically don't need ourselves to go up there because we don't really have that need for the very specialized talent. So we feel like we have everything we need in Montreal. Now we started in Montreal because we're based here, so that's very natural for us. We have actually office in Quebec City, one in Montreal.

But I think the level of talent and the recognition here is exceptional. And it's like the labor is extremely cheap compared to the us. So the economics makes a lot of sense here. And we don't really have that push outside for maybe capital, but very less true today. Much more capital that is accessible.

So I would say we don't really feel that pressure at all except when you're in the valley and they're like, eh, you're from Canada. Can you name like one Canadian company? Canadian company you can name, but like Montreal, maybe a bit less. So I think like we need, like successes bring more success. So if we can have multiple exits and we can like, basically have those like huge, like companies that are built here, like this will just bring more capital and more momentum.

So it's actually important to stay here and create our own success.

Mo Wrk: Yeah, so I, I agree with that. I just came back from San Francisco and I like, I just don't like that city. I don't like it anymore. It's not an animosity thing. I think like in the early days of the Valley, it used to be, it had this energy that was palpable and you walk, you would walk into any cafe and everybody's helping and supporting each other.

And now it's if you don't speak their language, if you're not like a multi-billion dollar whatever, then you suck. I'm not interested in that, and I think it's a mindset more so than anything else. I've raised over $50 million for my company here in Montreal, so it's not for a lack of access to capital.

There's great talent here. You built something great people come and work with you and for you. So I think it's just a mindset thing. And I think we need to stop thinking that we're small and we need to stop thinking that we need to sell and we need to stop thinking that like a billion is a great exit and all these things.

And like we really owe it to ourselves as a community to like really promote that message more. Especially to the early stage founders growing outta.

Nicholas: And I wanna get back to your original topic, Mo there, you could almost look at the infrastructure as a commodity at a certain point.

Is it just the rails and, the telecom rails almost that we're building on? Do you care about where those rails are located? 'cause you have a business to build and run and things like that? Or at what point do you say, no, this is core to us and we need to own that for our 10, 20, whatever year

Mo Wrk: future?

Yeah I think there's an a huge over reliance in the tech industry on rails being built for you by someone else. And then odds are often when we enter into a specific, new ecosystem like AI right now, or oh great, okay, the models are built, the cloud is there. So I'm just gonna go and build on top of that only to realize shit, I'm like spending 70% of my budget on, someone else's tokens and cloud.

And so we've actually pivot is not quite the right word, but adjusted our business focus to think through how can we help the deployment of AI and automation on rails that are agnostic of vendor and how can we actually create the right toolkits to create data sovereignty, to create security, to make these solutions be deployable on premises, on chip.

Think about like kind of the evolution, especially of robotics, who's actually building code today, or models that can be deployed on a specific chip so that you can now start creating your own machinery. So that's been really strong for us. And we're tying up with a large, another company outta the Middle East that's really pioneering this stuff. And I think that there's, in a world where like we got addicted to cloud, we have to unlearn that a little bit. And we have to, now that we are at this weird inflection point where we're already addicted to ai, unlearn the fact that maybe we don't need to rely on a model that's been built for us and instead be model agnostic and so on.

So it's a broad statement I'm making here, but it's now like this is the time now to make these types of calls.

Sylvain Perron: Yeah, I agree. And like for those who are young enough or old enough, you remember the early days of the internet, you wouldn't measure like what's your bandwidth?

What's your speed? And like we would basically care about how much ram you have and the megahertz in your computer. I think it's very early day for AI where at this point where I'm glad that many companies spend all that money. Like it's really capital intense to train models.

And I wouldn't want to like do that work myself, but I think it's really important that we have a balance of open source models that come that can basically offer this like long-term sustainability. Where, if one model provider goes down, like not half the startups goes with it, we still have a natural way.

Or CloudFlare. Yeah, or CloudFlare, this morning actually got that. We weren't part of that one, but I think, we should it is important to have alternatives, but at this point in time, I think it's way too hardy. The cycles are way too expensive and fast to be for at least for a company like us to be thinking about training our own models and offering that to our customers.

Nicholas (2): can add just one small element for companies working in the app layer focusing on bringing AI to an ICP, like a really a personalized experience for a certain professional. For example I saw Sam Altman two years ago, he was sitting right there. He said the future of AI is smaller models that reason much better and that, that have tools.

And that's what we do at Maxa, right? We pump up the reasoning and the general business knowledge. We give it deterministic software tools that can run through billions of records and do calculations. And we feel that the open source models and some of those models are getting to a point where they can replace just the reasoning engine and then your job is to orchestrate all the other stuff that's required around it.

So I think for people playing our space, like it's early days and actually I'm super positive 'cause I think we're gonna get even better tools, even cheaper and it's gonna be a kind of a revenge, so to speak. It'll, we'll and it's a big pie. Like rising tide lifts all boats. We need plenty of money to be made by everyone in that space.

Nicholas: Yeah, I love that. And that's like my thesis as well in a lot of ways. And leads into my next question. So if the models are commodities, open source and catches up and you can make an argument, open source, closed source, is there a gap between the two or for what's actually needed if the cloud providers are agnostic and they're a commodity as well?

We heard from Lara before at Mila saying that, get your PhD, get into venture, bring technology. What's your actual moat if everything's a commodity at the end of the day? Is it just data like Dom brought up at ameral? Is it some other secret sauce? Is it an actual technical sauce or is it just a go to market sauce?

Sylvain Perron: Yeah, you can go,

Nicholas (2): We see AI as software. It's a software component that needs to be part of a much broader software platform and specialize for a certain purpose. And that's where you create value. And we can swap in and out components every two or three years. Open source, not open source.

We lived, we're one of, I think the only startups in Montreal that's not sold or dead from the original wave, like 2020 wave. So that was ml, predictive algorithms and stuff happened. And then generative ai we kept saying ai, but like the type of people you hire, the skill sets they have are radically different.

So at some point it's components that you swap in and out and you have to figure out how you build and maintain your value around that. I don't think like the fundamental dynamic around that has changed just because there's a new really cool component you can add.

Sylvain Perron: Yeah, I'll go back to what Karin was saying earlier if you deliver true value for your customers, I don't see why they would be looking at switching software before switching humans, like humans and software have a 10 to one ratio in terms of cost.

And so I think as long as you keep delivering value and you have, like you, your customers don't hate your product, I think you're gonna be in a good spot. Now, in terms of like sustainable modes, I don't think software is gonna be able to create those kind of modes. Like you need to go outside in terms of distribution, access to capital and those kind of things.

For us, it's distribution in terms of who's deploying and learning our stack and deploying our software. So we go with agencies basically. So if you want to deploy, as an agency, AI globally, and you think in terms of like, how can we do that to a hundred or a thousand clients, you need to learn one stack and, have a go to.

And so we basically rely on the fact that like employees will learn, like one tool and basically keep, deploying that tool for a few years at least. And once you have an installed base, I think as long as you keep having a really good product and your customers don't hate you, I think they like, they won't really try to switch off.

Mo Wrk: All right, bear with me because this is just like stream of consciousness. I have so many in inputs that are coming at me from just like all the stuff that we see, because again, we're not an AI company. We're an AI deployment company. And so we see sort of technology being deployed in the workforce in a multitude of different ways and formats.

So I'll start with the easy one. I think traditional SaaS, in my opinion, has died or is in the process of dying. And I don't know why anyone would still use a Calendly or frankly a DocuSign or anything like that when I can probably recreate it overnight with a cursor or something like that.

If you're a lawyer's office and you're paying $50,000 a year for DocuSign, do yourself a favor and just rebuild it. I, that's just my point of view. So I think these traditional types of SaaS models and SaaS businesses are going to be really difficult to compete from a technological competitive mode because it just doesn't exist anymore.

And so in that world, I think it's sales, marketing, distribution that still wins. So if you know how to own the customer, own the niche, provide a very high level of customer service, and make it so that the price point is so unbelievably cheap, where I don't have to ask the question, should I rent or should I build, that'll stick.

So that's in one, one arena. The other bit that I'm starting to see is there are certain companies that are starting to develop these very sophisticated. Kind of solutions and toolkits that are actually winning on technological sophisticated and advancement. And these are companies that have research labs, literally internally doing the kind of operational research the deep tech stuff that, is starting to gain a lot of attention within the VC community, which I think is highly interesting and exciting because we're getting back to actually developing real tech and not wrappers on tech.

And then the third, and maybe last thing that I'll leave you guys with is I feel like we're at like really, again, this interesting intersection, and I always call for revolutions, so revolution. But I think we have an opportunity where technology today can really help enable the small, medium sized businesses become bigger.

And in a world where large enterprise has an opportunity to completely wipe out all the SMBs because of all of the traction they're getting with AI and all the, all of the money available to them, I think that certain companies who can be enablers to the SMBs to grow bigger. So from S to M and from M to E, if we can enable them with technology that make them bigger, they become addicted to these types of technologies.

And that becomes your competitive mode because you're just allowing them to grow and scale. So it's like a widespread thing. It's all over the place, but yeah. Revolution.

Nicholas: Love it. So we're almost at time, so quick rapid fire in all your go to market and enterprise discussions and whatnot.

What's the most over hype thing you're learning from clients right now? Or you just wanna kill this Bud Buzzword ai.

Music: Ouch.

Nicholas (2): My, my favorite is still agents and agentic. That's my favorite. Yeah, me too. And that's what I sell. So it's a good

Mo Wrk: thing. I just, sorry, just a anecdotally, just because I came from the valley, we actually, I just, I have like in my phone, probably 30 different pictures of billboards with.ai, like caffeine ai, unicorn ai.

So I have all of them. I'm making nice little funny meme out of it afterwards.

Nicholas: Whoever, which country owns the AI domain? They're doing, I think it's Antigua or Anguilla,

Mo Wrk: I forget.

Nicholas: But they did 30, 40

Mo Wrk: million bucks in just domain registrations. It's not bad. Alright.

Nicholas: Thank you so much guys. Give it up for them.

And with that we are onto keynote time. I'd like to invite up Sam and Fred to wrap up the evening and then community ask,

Fred: awesome. Thanks Sam for being here. Hi everyone. Big congrat to the AI salon organizers, by the way, like amazing job. So we're the final talk before the beer, but we'll final talk of the year as well for AI Salon.

So that's a bit of pressure. So then today, tonight one of the ask was we gotta inspire the community. And I heard some of the panelists before say we, we need SI think was saying, we need more exists. We need to see more generations of founders who build sell than get back into the ecosystem.

And that's why I'm so happy that to have you sitting next to me and obvious, obviously, Sam you're, today, you're co-president LA Zero alongside yo Schwab and Geo, but you're more, most known for your work at Brainbox ai which was acquired not even a year ago now. Yeah, January. Yeah, January.

So I think one of the thing that would be interesting to talk first is is your background getting there because you are trained as a lawyer, worked in law in MBA and got to private equity and then joined a startup, which is not the normal path like that, at least for most of the people here.

You would think you're a geek coming from tech or from Mila. So tell me a little bit how

Sam: did you get there? Yeah. I feel number one that my wife should be sitting right here to answer this question 'cause that was an important moment. So yeah, like the bulk of my career as thank you Fred for the question, and thank you for having me here.

But the bulk of my career was traditional private equity, which means like shit, anything from a steel plant to a manufacturing to et cetera. So pretty far away from tech. And but I did have this moment this was in 2017 where I met with Jean, who was the CTO, but the brain behind Brainbox ai.

And and we by happenstance had this meeting and then he was telling me what he was working on and basically the idea was let's use autonomous AI and plug them into the heating and cooling systems of buildings. And that sounds really boring and it sounds very niche, but we spend an immense amount of energy on this planet, heating and cooling our buildings.

A whole bunch of it is wasted just 'cause of the way the systems are designed. And when you think about autonomous ai, we know, we mostly all know it as a self-driving car. The ability to have this brain learning a very complex system, and then to make thousands of decisions every hour of every day to make smarter decisions than what this basic system does is it was an immense opportunity on my side in private equity when we used to buy a plant or a facility.

We try to save one or 2% of energy and spend all kinds of millions of dollars and put together a team of 10 engineers to make it happen. And here's this crazy nut who says, I'm gonna put a software on top, an AI driven software on top of this complex industrial system. Now I'm gonna save 15% and 20%. And I said, that's why I fell off my chair.

That's where after doing some work, I went home and had a conversation with my wife and said, yes, I am quitting a stable job. Yeah, we have four kids, yet they still have to get through school, but we're gonna do this. So that was the moment you,

Fred: And I think there were a dozen employees at the time at Brainbox, right?

So not only you believe Jean Mall and joined that venture, but you knew that buildings is probably one of the worst place to try to implement ai. So there's legacy systems all over the place. Legacy protocols that are like 40, 50 years old. And you're selling, so tell me how your background maybe helped you sell to building owners and building managers who are.

Maybe the least tech savvy people that you can sell to.

Sam: Yeah. So some of it I didn't know when I joined, so you learn along the way. But I will say this. Yeah, the background was really helpful when you're presenting to someone who's so far away from technology, especially ai, to talk their language and to talk, beyond just even ROI, but present to them an opportunity that they hadn't even crossed their mind that, these systems are working anyway, so why bother?

We were fortunate, we consider ourselves a climate technology company and that these real estate owners, very traditional when it comes to tech adoption, suddenly are getting pushed by their investors on the top end and by the big customers, big lessees on the bottom end saying, what's your sustainability plan?

And so then if you can come to them and show them a path forward, bring down the tech talk, right? And get to selling what changes day in and day out is a big deal. But that was, that what I would say was probably one of our biggest challenges. I thought it would be the ai, but it was actually that.

Fred: So I like this kind of dual mission, right? Obviously bringing AI to to a new sector, to a new industry. But this climate pledge that the company has had from the beginning. And I'm wondering from your standpoint. Which one was the first driver? Was it we're doing, we're building new AI technology and oh, it happens that it will help climate or was we need to fix this climate problem and all the energies that is wasted by buildings and AI was a tool to do it.

Sam: I think we were an AI company. Like we weren't gonna do this unless we could make that, that AI work. And what I didn't realize at the time, the autonomous car, everybody has seen it. They were promising. Who was saying it? Take, I've been to two weeks of closing. You have been the two weeks of closing for the last year.

It's the same thing with the autonomous car. It was promised seven years ago and then five years ago, and then, and now maybe we're finally starting to see it at some scale. So for us, using autonomous ai, was harder than I thought jumping in. But that's what had to work. Or we had nothing.

We were not gonna do just another dashboard in an industry that had 20 dashboard companies. So we had to make it work at the same time. We were competing for AI talent like every, everybody else. And we were an incredibly mission-driven company. I look at the climate issue, sorry, I'm gonna spend 30 seconds on climate.

I look at the climate issue. The big buckets are how we grow our food, how we make our energy transportation. The four or five big buckets you always name. I still think the one we were working on is one of the last to come to the table, right? Electric cars are coming at a big time.

Batteries are getting cheaper. Solar power, renewable, all cheaper. It's all coming. No one's building a coal plant anymore. But what we do with our buildings and probably food, is the two that are left over. So when we were pushing it and getting to a solution, we weren't surrounded by 20 other companies trying to really build a scalable solution in our sector.

And so that was a big motivation for the team. A big way. We were able to attract talent to make it work.

Fred: Nice. And so if I come back to the whole journey or it was what, seven years I think from your joining to becoming CEO then exiting to train was it an overnight success? Like when did you feel, okay, this is working?

'Cause obviously extremely complex deployment very difficult to win customers trailblazing, new technology. So did you always believe that it would go through or there was a haha moment at some point?

Sam: Good question. I think you live, every startup will live through that. I don't know that it was like, I don't believe it or I'm not sure.

I'm not sure. And then I suddenly, I think we, we definitely had waves. I think the tenacity to pull something off that hadn't been worked on and made a success, kept us going in a big way, even through the challenges. We know, I think we fundraised well and had the capital to, to see it through.

It sounds very crass, but that's the reality of it, right? You've seen it multiple times. So I think we just fought our way through, through the ups and downs. We didn't have a, an aha moment. The buyer today, huge supporter of the technology, huge supporter of the Montreal AI ecosystem.

We should cheer ourselves more than the outside people. Cheer for us. Absolutely. Yeah. Okay. And and so the continues in the investment in the technology, they're gonna grow the office here, grow the team here. That's all a testament to that tenacious push to make it happen. We didn't, unfortunately, some days I'm like, why didn't I just make another dating app?

'cause you go boom right away from 10,000 users to 2 million users when you're doing AI for the real world industrial, et cetera. You do not have that like whammo. But at the same time, frankly, we were alone out there at having gotten to that level and we were just gonna see it through.

Fred: And pretty supportive investors at Brainbox as well.

Mostly local, if I recall right, we started

Sam: off very local. Yeah. Then we ended up with with a BB outta Switzerland as a big one.

Fred: And I was an investor dynamic in the context of this technology and growth and revenue and metrics. And there's climate, right? Like this dual mission. How does it work when you have investor discussion?

Sam: I think the one element we had working for us was that it was such a monumental problem and I don't know, give us like the battery technology sector such a monumental importance. They're now growing like crazy, et cetera, but there were 30 companies working on it at scale, right? And and some of them are no longer here, et cetera.

Unfortunately, one of the ones we bet on here locally is no longer here. But I think what we were able to push was just the uniqueness of the technology and that we didn't have one or two people behind us and we were tenacious and we weren't gonna give up. The investors if they could look at us and say, but hold on a second.

Why did, why are they making progress or why, the mission was super important. The outcome was super important and we weren't gonna stop. So I think that kind of belief helped us work through any tough investor discussions we had to deal with.

Fred: Nice. So let's look at the future a little bit.

You, you could have done anything after Brainbox, right? Like you could have started another company startup. Another startup, yeah. You did another startup. Yeah. And you decided to join Law Zero. And I want to hear a bit more about Law Zero, but one of the thing of Law Zero is it's a nonprofit. So again, switching gear a little bit, even though that it's very techy.

So give us a little bit more about what's Law Zero and the mission as well There.

Sam: Okay. And in answering that, I definitely want to get back to, as to the

Fred: non-profit discussion,

Sam: to supporting the ecosystem. Yay. Okay. Please, let's make sure we come back to that. I I learned about the law Zero effort.

It was publicly announced in June, but I had learned about it a few months before. One of the motivators as again, the use of autonomous ai, still relatively rare. Okay. Self-driving car. We are now seeing it in a maybe more challenging environment, which is the military. That's a big question mark for society as we were doing it.

And seeing the capabilities like Jean cmo the original idea man and CTO and I would have discussions along the way. There is very little dangerous about putting autonomous AI into the heating and cooling system. The worst it could do is make us all sweat or make us all freeze and we wanna leave.

But there's very little risk. But as you saw it go, you saw, okay, we're entering into a brave new world where this brain is learning and then making autonomous decisions on a grand scale. So we started having conversations just on the side about what, what likely would play out, et cetera. So that was our look into AI has amazing fantastic potential in many sectors.

But the Spider-Man movie with great power comes great responsibility. And and then generative AI came along. And then as Yoshua Bengio, Jeffrey Hinton in Toronto and many others started raising their hand and saying, yeah, we invented the damn thing, but guys, there's an issue here.

And I learned that Ywa decided to launch. So Ywa is the founder of this whole thing we're sitting in right now open research big institute. He decided, other than just talking about it, which he did a lot and continues to do. I go, I'm gonna spend the rest of my career coming up with a technical solution about how we can take these new large language models and make them safer and more reliable and more trackable than they are today.

'cause frankly, today, they are none of those three. And so when I learned about it, I go okay, here's a way to to jump in and give back. I'm an exit gives you freedom of choice at a certain point. Like I said, I had four kids, they're still going through university now. I could do so a little bit more comfortably.

Decided to to jump on this adventure and give that same entrepreneurial 'cause. It is a, we're taking a, someone from a research institute and a whole team from a research institute and said, we're gonna develop a product and we're gonna do nothing good if we don't have a product deployed in the field.

And so when they, when I heard they needed at least support on that side, I said, okay, I'm in.

Fred: Very ambitious, very important as well. But you're in some way, it's, I wouldn't say adversarial, but still you, there are forces that are investing billions and billions in the opposite direction, right? In, in like trying to bring autonom AI in military and things like that.

So how do you fund such an ambitious mission?

Sam: First you drag y around and you make him speak. I'm sure it helps. Yeah, it helps. It helps a lot. I walked in the door, they had already funded fundraised a fair amount of capital and we continue to do and the persona helps. We're looking for free money basically.

And, the donations and we've had good support. Some of them are public. There'll probably be a few more announcements, but, the Gates Foundation, Schmidt Science, et cetera. So the same people that are also pushing the excitement around AI also are realizing that there's a risk here.

So I think that's why they're doing it. And so far, they're giving us less money than they're giving the big push in ai. But we gotta prove ourselves and edging their bets edging their bets, maybe. But but look, I think there's an easy point to, in this case here, if deep seek didn't exist, the only ones who did something amazing would needed 10 30, $50 billion deep seek showed that you could do something pretty good, pretty amazing with, I don't know, people argue about the money, but who cares whether it was 50 million or 150 million?

It was still a fraction of the to, yeah.

Fred: Thanks. So let's switch gear to supporting the ecosystem. And we were talking together about like the gravity of talent in Canada. But I know you're coming back from Europe and you were like comparing the ecosystems and if you can repeat a little bit that Yeah,

Sam: sure.

Sure. So the one thing, just to put a little bit of context behind that question, it always drives me to drink. And here's all the beer drive me to drink when I go abroad. And people don't know that one of the main cities of creation of modern AI is here in Toronto. Okay. They don't know it. And it just drives me nuts.

That's one. So we gotta do a lot, hell of a lot better tooting our own horn, do some clever stuff, but people have to know the depth of talent. So that's one. Then what Fred was referring to, we just did one of those roadshow where you're dragging Joshua around tiring him out for a couple of weeks amazing meetings and everything.

But Europe's trying to, so the middle powers China, us and us middle powers are trying to figure out how do we maintain our sovereignty of AI and don't end up in a corner between those two giants. Europe is on that question heavy. They're gonna, they're starting to fund compute supercomputers, et cetera, et cetera.

But they're like, we need to build a sovereign labs that create our own ai. And I was actually surprised in that I've learned in the last couple of months that, a lot of their Europeans, like our Canadians, went down to the US but I think it's worse in the European context. And I walked away out of that trip with the following conclusion.

You take all of Europe together, take out Google DeepMind based outta London, Demis Hassabis. You remove that from the picture is US owned, and so therefore part of the US ecosystem. I don't think that there is, I think there is less talent of across all of Europe than there isn't this very building?

That was my conclusion. Yes. And I and the interest. Exactly. We need to clap and shout it. And we got Vector in Toronto. We got Amy over there. We gotta we, we have an incredible amount of talent. We gotta use it. We gotta sell it.

Fred: But now what do we do with it?

Sam: Yeah. What do we do with it?

Yeah.

Fred: And I know you're giving back in many ways as an investor, a coach, and to, to many companies. So applaud you for that. We need much more many more individuals like you giving back. So this is quite amazing.

Sam: Yeah. And I'd like to comment like, there is a wave happening right now by the way.

So your very fund I think is a wave very it's public. So I joined the fund as well as an lp. I think it's fantastic that we get all the entrepreneurs around an effort like this and we should probably push that even harder. That's number one. The gentleman that spoke about Mila before, there is a real push, I'll tell you internally around the Venture Studio and making sure that we push more startups out of this institute.

I hope Vector's doing the same. I hope Amy's doing the same. So I think there's a real movement and I see a lot of progress. I've only been in this building four months with Law Zero and I see a lot of movement. So there are things that I get excited around. Was really happy to see the $1.7 billion in the federal budget to, to get talent back into the country.

So I think I see pieces coming together. So the ambitious ambition is growing and I think everyone needs to get behind that and

Fred: we're bullish on what's happening in the building too.