Yeah, I’m struggling a little bit this Friday afternoon. If you aren’t in the United States, it’s a little hard to explain. In short, certain deficiencies in our policing and judicial systems flared brightly as the week came to a close. So, today’s Exchange newsletter will be shorter than intended. Hug the people you love, and everyone else. — Alex
The DevOps market is busy and well funded. For example, I caught up with Opslyft the other day. Straddling India and the United States, the company is building a unified DevOps service that brings together tools that are for the post-deployment side of creating software. It’s a neat company and one that I will probably spend more time writing about when it announces a capital raise. GitLab, a pre-deployment DevOps service, went public recently, to pick another example from memory.
All that’s to say that tech companies big and small are building DevOps tooling. And we’re seeing the machine learning operations (MLOps) market start to ape its larger sibling pretty quickly. TechCrunch noted that MLOps startup Comet raised this week, which reminded The Exchange that we recently took a look at the recent Weights & Biases round, another capital event for a MLOps startup.
I bring all this up because we caught up with Sapphire Ventures’ Jai Das the other day to collect more context for our piece looking into AI fundraising trends. During the chat, I brought up the idea of AIOps and if that was going to become a third "Ops" category for us to keep an eye out for. Per Das, however, “MLOps is basically AIOps,” he said, so we can mostly constrain our thinking to the two main categories.
That said, AI and ML are not precisely the same thing — let’s not get into a fight here, I’m speaking loosely — so it will prove interesting to see if the two different types of work can sit inside the same basket of software.
More on AI
Sticking to the AI theme, we have a touch more on the AI market for you this morning. Anna has notes to start, building on our recent entry discussing artificial intelligence investing trends around the world. She has thoughts concerning where AI funds are being disbursed today, and how changing definitions of what merits the “AI” moniker could lead to a wider dollar footprint for the startup activity:
While the geographic disparity caught our attention, we expect dollars to be more evenly distributed as the definition and applications of AI broaden. For instance, the two newly minted Latin American AI unicorns in Q3 were NotCo, a food tech company, and Unico, a digital ID provider, while a major round also went to Mexican lending company Kueski, which we'd have called a fintech but is also AI-enabled. If that's the new reality of AI, we wouldn't be surprised to see more money flowing into startups leveraging it to tackle real-world problems anywhere in the world, including in Latin America, but also in Africa.
To close out our AI work until next week — if you live in Canada, we have something coming that you’ll want to read — here’s an answer from Point72 Ventures’ Sri Chandrasekar that came in a little late for our last AI article, but that I wanted to share all the same.
Responding to our question about AI-focused startup economics, here’s what the investor had to say:
In my view, most of the recent interest in AI has been driven by revenue growth of companies that are raising large rounds. But the reason behind that revenue growth is pretty simple: high demand for products and low labor participation. We’re seeing this across the Point72 Ventures deep tech portfolio. AI has the ability to augment humans and make them more productive, and in some cases, replace them in tasks that are highly suitable to automation — freeing them up to focus on more value-add, strategic activities. Historically, the friction to introduce this automation has been high, but when you can’t hire someone to handle a customer service request or to man a desk, automation suddenly becomes a lot more interesting.
We’re learning a lot lately about how macro conditions can impact startups. From rising inflation dinging insurtech margins, to the Great Resignation driving demand for AI software. Something to keep in mind.
Other things that matter
And speaking of mega-rounds, Faire raised a Series G this week. So what? Well, it had some interesting growth stats to share. Faire, in its own words, is an “online wholesale marketplace,” a business that is growing rather quickly. The company self-reported “3x” revenue growth and more than “$1 billion in annual volume,” which caught our attention. The company would be an IPO candidate if the private market wasn’t busy trying to turn it into venture capital foie gras.
What else? OKR startup Koan wound up selling to Gtmhub after failing to raise a Series A. On a less busy week, we would have dug more deeply into the matter. But since we’ve written about the OKR software market so much over the years, I did want to flag the event. (Koan’s CEO was kind enough to share some notes on the end of his company, both publicly and via email, so we may have more next week on the matter, time depending.)
And, finally, Braze. New York-based software unicorn Braze went public this week, and The Exchange caught up with the company’s leadership on their IPO day. As with all IPO calls, the company in question was under pretty strict guidance regarding what it could say (not much) and what it could not (nearly everything). Still, we got some notes on its prep process, namely that the company started to get ready for its IPO a few years ago, but started the real process of actually going public about a year ago. We wanted to know why the company — which hadn’t had to raise money since 2018 — hadn’t pursued a direct listing. Braze CEO Bill Magnuson told us something interesting, namely that the traditional IPO is not as inflexible as some folks think, in light of recent changes. That’s worth thinking about as we see the final public debuts in 2021 over the next few weeks. Braze, we should note, is now worth $94.16 per share after going public at $65 per share.