Resolve AI, an AI company that was started by ex-Splunk executives, has just hit a 1 billion valuation, as they just raised their Series A.
Today on the podcast, we'll be talking about where we see this company going in the future, what they're doing today, how they got started, how they reached a billion-dollar valuation and everything you need to know about Resolve AI.
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Let's get into the episode.
Resolve ai just reached a 1 billion dollar valuation.
This is a startup that is building an autonomous site reliability engineer or an sre.
Essentially it automatically maintains software systems.
This is their series a that they've just raised, and it was led by lightspeed venture partners.
There's a bunch of people that are looking at this deal that have kind of been putting off these uh hints and tips on what's happening, but obviously lightspeed ventures is a major vc firm, so it's kind of top tier what's going on.
One thing that's interesting in this deal, according to a bunch of people that are kind of insiders, is that like technically, the headline valuation is that it's a 1 billion dollar valuation, but there's actually a bunch of different um levels to this round.
So there's kind of a multi-trenched structure.
And under that, many of the investors bought in at a lower valuation than a billion dollars.
But the kind of final investors that came in bought in at a billion dollars.
There's actually a lot of rounds, a lot of like fundraising that will do that.
They're like hey, you know, for our first hundred million dollars, we'll do this valuation for the next hundred million dollars.
It increases or, you know, a hundred thousand for smaller companies.
And it kind of the people that get in later are getting at a. higher valuation.
This is to incentivize the early investors to kind of get in and to get their term sheets written and done fast so it can build momentum for the round.
It's an interesting structure to see on a bigger company like this, because I see this a lot for smaller organizations.
But in any case then by the time the whole round's done, even if there's only a small amount of people that are signing off on the investment at the 1 billion mark, they can say we've reached a billion dollar valuation.
And then anyone that got in earlier, it's like their shares are instantly worth more as well.
So I do think this is interesting.
Investors said that this kind of structure has become really common for the most in-demand AI startups.
We're seeing more and more of these.
Resolve AI's annual recurring revenue is about 4 million right now, which is great, considering this is a company that was founded less than two years ago.
It's led by a former Splunk executive, Spiros Exanthos and Maya Argoal, Splunk's former chief architecture for observability.
And both of them have known each other for like 20 years.
They go back to their graduate studies.
They both went to the University of Illinois Urbana-Champaign University.
So this is not their first startup together.
They previously co-founded Omnition, which Splunk acquired in 2019.
So traditionally, human SREs are given the task of manually diagnosing and fixing system failures.
Resolve AI right now is hoping that they can automate all of that by autonomously identifying.
Well, first it identifies, then it diagnoses, and then it will go and resolve the production issues.
And it does all of that in real time, which is really impressive.
And so they're really trying to address this growing pain point that a lot of companies have as software systems grow more complex and they are increasingly distributed across cloud infrastructure.
Organizations have this problem where they really struggle to hire and retain enough experienced SREs to keep everything running smoothly.
So.
Because of this, automating all of those responsibilities cuts a lot of downtime and it also can reduce operational costs.
So, at the end of the day, I think a big part of the value proposition is that they're allowing engineering teams to focus on building new products instead of constantly firefighting production problems.
This is just something that's a classic startup problem where, if you build too fast and your systems aren't built properly or there's, you know, issues with the current code or system, then it essentially delays you from being able to build anything new and innovative, because you spend all of your time maintaining what you had in the past.
You know, there's tech debt, there's things you got to go back on.
And I honestly think that...
A phenomenal thing that humans are really good at is dreaming up new, exciting, creative ideas.
And if they can especially you know, maybe build wireframes or simple versions and have the AI go and make these really hard.
You know case and you know tested versions of that code that work really well.
That would be a phenomenal use case for AI and code that I see a lot of people could get excited about in the future.
I think they're a piece of this puzzle.
Last October, they raised about $35 million in their seed round.
This was led by Greylock, another tier one VC.
They had some participation from World Labs founder Fifi Lee and also Google DeepMind scientist, Jeff Dean.
I think right now they're competing with Traversal, which is another AI-powered SRE startup.
They also raised a lot of money.
They raised, I think, about $48 million in a Series A, which was led by Kleiner Parkins.
They also had participation from Sequoia.
So this is a hot area.
It's being invested in by all of the top companies.
And there's a lot of really smart minds working on this issue, which I think just goes to show this is a real issue that they're solving.
It's a real pain point.
And if they can crack this, a lot of people are going to be very excited.
Thank you so much for tuning into the podcast today.
I hope you learned something new.
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I'll catch you in the next episode.
