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Resolve AI, 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. Before we get into the episode, I wanted to mention if you want to try all of the AI models I talk about on the show and you want to do it for only $20 a month, I would love for you to check out AI Box AI, which own startup. I give you access to over 40 of the top models including everything from OpenAI, Google, Anthropic, 11 Labs for audio, a ton of great image models, all for $20 a month. You can go check that out at AI Box AI. There's a link in the description. 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 just raised and it was led by Lightspeed Venture Partners. There's a bunch of people that are looking at this deal that are kind of been putting off these 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 one billion dollar valuation, but there's actually a bunch of different levels to this round. So there's kind of a multi tranched structure 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, the people that get in later are get in at a higher valuation. This is to incentivize the early investors to, to kind of get in sheets written and done fast so it can get build momentum for the round. Is 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 you know, by the time the whole round's done, even if there's only a small amount of people that are, you know, signing off on the, the investment at the 1 billion dollar mark, they can say, we've reached a billion dollar valuation. So. And then anyone that got in earlier, it's like they're, you know, their, 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, Spyros Xanthos and Maya Argual, 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. So this is not their first startup together. They previously co foundered Omniten Omnishan, 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, it's a classic startup problem where if you build too fast and your systems aren't built properly or there's 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, 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. So I think they're a piece of this puzzle. Last October, they. They raised about $35 million in their seed round. This was led by Greylock, right, another tier 1 VC. They had some participation from World Labs founder Fifi Lee and also Google DeepMind scientist Jeff Dean. So 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. Um, it's being invested in by all of the top companies. And there's, you know, 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. If this was interesting or useful, make sure to leave a rating or review on the podcast and as always, make sure to go check out AI box AI to try all of the latest AI models in one place for $20 a month. I'll catch you in the next episode.