Université de Montréal - HEC Montréal
Master's Degree, Business Administration
École Polytechnique de Montréal
Bachelor's Degree, Computer Engineering
In these jobs, I was building software systems that were close to electronics. It had to do with signal processing and how you interpret those signals with respect to product design and manufacturing.
Weirdly enough, mastering is also signal processing. The difference is that the information mastering describes isn’t the health or functioning of a product—it's the signal that you're going to be listening to. From a mathematical standpoint, it’s identical to what we do at LANDR.
From a building blocks standpoint, what made me consider LANDR was (a) that the technology, the core technology, which was prototyped at the Queen Mary University of London, already existed. So there was a starting point. And (b) was that since the product existed, I could judge it from a technical perspective, as well as present it to people and see how they reacted. From there, I started the company with two other guys, one of them being the lead researcher who moved from the UK to Montreal.
So my technical background enabled me to move into a new domain. I have also always been a fan of high-quality music production and sound systems, so mastering—the process of getting a product to the highest quality—was attractive to me.
Truthfully, it took me a few years to understand consumer reactions to LANDR and what specific creators liked and didn’t like. So we had to pivot. In the end, what we launched what much different than the original product.
Yes, progressively. The positive sentiment has been steady for a few years, but now we’re seeing that AI mastering is becoming fully accepted for specific purposes. When we started, sound engineers were skeptical. But many musicians who had previously hired sound engineers or tried to engineer music themselves were receptive to LANDR’s audio quality and affordable price point. We never tried to attract sound engineers. Our goal was to provide something for the majority who can’t afford mastering because they don’t make money from music.
Within six months of launching, many producer-DJs got in touch with us. They found LANDR useful because they could make changes to their songs from one night to the next and have a mastered product ready to go without waiting on an engineer. So the fact that the service was near-immediate was a big deal for them.
LANDR allows for iterations. And surprisingly enough, we created mastering as a subscription...a process you repeat often. Now, mastering is not something you do when you are finished with a song, but something you should do to evaluate the progress or state of a song.
That's a good question. Let's put it this way. What we are trying to do is empower music creators and connect them with other creators. We want to make it easier for creators to learn so they can stay focused on the creative process, without getting caught up in technical stuff. We also want to minimize the amount of information creators need to read to finish their music and make money from it. This all leads us to look for simpler audio plug-ins and intuitive ways to curate samples for them to produce music more efficiently.
When we look at the creative process, the DAW is at the center of it. When we started building LANDR, we wanted to offer an AI-based mixing environment as well as a mastering environment. In the end, we cut out the mixing to focus on mastering because we found that consumers were less likely to let go of their favorite DAW (Pro Tools, Ableton, etc.). The attachment is too strong, and it felt like it would be an uphill battle to win over customers.
Instead, we focus on bridging the gap from DAWs to listeners and build compliments to the creative process. Right now, I don’t see us being an active player in the DAW market, but this might change in the future, and we will have to think about competing.
Exactly. That's what we do. We also ask our readers what they'd like to learn about and study their challenges. Their fields of interest drive how we choose rent-to-own plug-ins. The goal is to simplify the life of creators and remove any friction that stops them from creating.
Well, we are much broader than other AI mastering competitors, but Splice is one of the best competitors we have. With samples and rent-to-own plug-ins, we moved into their field. But regarding AI mastering, LANDR is the only platform that can claim to have AI. We have tested other platforms marketed as AI, and their solutions are algorithm-based and linear. It’s not machine learning-based and is a much simpler logic. The other thing that helps set us apart is the amount of money invested into LANDR. Other companies don’t have AI because they don’t have the teams to do it.
With samples and plug-ins, we're diversifying, but we are also creating a platform that does everything a creator needs after a DAW. This way, we optimize the commercialization and sharing of music, as well as the relationships between creators and the people who can advance their careers.
One trend is the acceptance of AI as an assistive tool for people making music—specifically to automate processes or to help in curation.
I think the reliance on samples and stems in production is something that people now accept too. Bands are going from five members to three to two. This makes the combination of vocalists and producers more frequent, and makes it easier to go to market. We noticed this trend and decided to become an active participant (with LANDR samples).
The other trend I’ve noticed is that the collaborative approach to making hip-hop has spread to other genres. People are turning to singles and away from albums, and as they do that, every song becomes a business opportunity for a joint venture with other artists. So we're trying to facilitate this and treat every song as a product on its own.
We see the song as the central piece that everyone gathers around—whether that’s through samples, people collaborating, or session musicians. LANDR is making the entire process totally frictionless.
Exactly. The composition process has changed. It’s not as focused in recording anymore. It’s a lot easier. You can pick the hook from a sample library and go with that, which makes the role of the producer more accessible. For this reason, producers who can do something new and come up with results that are hard to replicate are increasingly valuable.
LANDR is helping support this trend with an AI-based recommendation tool for sample selection, as an input into your DAW session. It’s the first iteration and we will make it better every quarter.
A misconception is that data is replacing what the artist does. At their core, artists are artistic directors. They have to make a lot of judgments and decisions. They are also performers, which is a different role that requires the ability to interpret something. This is artistic too, but in a different way. Take a cover song, for example—the original might be great, but the interpretation might not.
So I think the biggest misconception is that data is a productivity source. When data is used to replace a human, what you do with the data, and how you interpret it, is what’s important.
AI-based mastering isn’t taking the role of a human, it’s giving more power to a DAW. Most mix engineers will use LANDR to come up with a master, and when they want something different, they’ll go back to the song to make changes, and repeat the process. So there's some guidance, but you still have to mix, right?
The reality is that there's just too much money around. There are too many projects. The demand for expertise is going faster than the ability to supply the expertise. So what used to be a competitive advantage is less so for an entrepreneur like myself.
For knowledge workers, they have more options than ever. But for the marketplace it’s becoming more expensive to do business here. There are subsidies for Google and bigger players that can come here, when nowadays, they don’t need to do that to come to Montreal.
So the ability to reach a critical mass and be competitive with bigger, sophisticated companies is difficult. Funding becomes a critical element that you need to get, that you want to be able to compete.
I'd say it's mostly two things. One is the opportunity itself. As new companies come in, market dynamics change and opportunities open up. So when I get exposed to a business opportunity that doesn't look occupied, that excites me.
Second, when the person carrying that message is ambitious and has the appetite to build something, I feel more attracted to that business. When I see the combination of the two—especially when the entrepreneurs have read a lot about the market, their competition, and have a mature market strategy—I become very interested.