They were going to do some 'consulting' type work, and then ostensibly use the results of that to come up with product offers.
The obvious fallibility in that is:
1) The companies they are working with will not give up their data and allow them to be used in Element Products. No way. In some cases, maybe for a fee, but in most cases it's not even viable.
2) Making viable products is really hard. You don't 'start with AI and then pick a field'. You need to understand the industry, the channels, develop relationships, develop a brand etc. and have something that's really hot.
Element eventually launched a handful of bland, generic off-the-shelf style AI products for image recognition and a few other things, each one a little bit interesting but ironically none of them worthy of really being a startup on their own.
3) Consultants and Researchers are not Startup types. Of course they can be, but not by default. Definitely some ex-Phds and ex-consultants could launch a great company, but otherwise hiring a bunch of them for big salaries and putting them in a room is not how startups form.
They work really hard, they are really smart, but they're not generally very good at finding seams and opening new markets.
4) Generally the way it's done is 'start small' and when there is 'product market fit' you scale. So Element didn't fit that model. They took on $100's of millions before any kind of product-market-fit and ran around in circles burning it.
It would have been nicer to start with a team of 10, find resonance, then start to pull in the talent.
But in some situations, raising $150M with government and institutional backers is easier than raising from traditional VC directly. Like a big government backed initiative with all the flair, PR, announcements.
The CEO of Element was literally on a public Zoom with the PM of Canada recently.
That kind of company.
The >$150M raised, a good chunk sourced by the provincial government, is in a sense more "precious" because there's so little Canadian venture capital with low(er) risk tolerances floating around, resulting in yet further tightening of Canadian VC capital. The problem compounds itself.
No VC - even American one's were going to invest in that kind of boondoggle up front at those valuations.
So you're right when you say 'there isn't enough money' - at the same time, that's not the problem specifically here, and, frankly, good companies will get the money.
There are big funds in Canada.
But it drew attention to the AI scene, universities received massive funding in AI which is fantastic, startups grew around it, VCs started investing more in MTL(not only because of them, but it did play a role), FAANGS expanded their offices and openned AI labs downtown and in the mile-end.
I was not a fan, but the publicity they received has definetly been good for the scene.
