Today on the podcast, I want to talk about a startup that just raised a $10 million pre-seed, which is called Julius. It's basically an AI data analyst. And the thing that I think is really interesting here that I think is going to be like exciting for the whole industry is just how much controversy and I guess pushback this company had at the beginning when they were first getting started, because basically they're a data analyst. They do something that ChatGPT has built in.
And anytime the ChatGPT or any of these foundational models, they roll out a new feature set, right? Like, you know, voice, or they have kind of agents built into ChatGPT. People say, oh my gosh, the agents built into ChatGPT just killed 400 AI startups. But at the end of the day, it doesn't actually have to kill startups.
And so today on the podcast, I want to be breaking down what happens in an industry when you still focus on a small vertical like this, what basically the outcome has been for Julius and where I think this is going to go in the future. Before we get into that, I wanted to mention, if you've ever wanted to try any of the top models that I mentioned on this podcast, I'd love for you to check out AIbox.ai, which is my very own startup, which is currently in beta. On the platform, one of the things I love, you basically get access to the top 40 AI models all for $20 a month. You don't have $20 subscriptions to everything.
But we have a section there, which is basically the benchmarks. It shows you the price per AI model compared to using it against other AI models. And also the quality, which one has the best score basically on the benchmark. So if you go over something like Sonic 3.7, you can see basically how much it costs in comparison to other models.
It's kind of up there because it's their top model. But you can also see that it is the highest score next to a lot of others. But you might be surprised that the Quen 2.5 model isn't actually super far behind based off of benchmark scores at 7.7. So you also can find, you know, Gemini is kind of competing well against it.
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All right, let's get into what's going on with this AI startup, Julius. So just raised $10 million in the pre-seed, like I mentioned. What's interesting is their CEO is like sort of low-key famous. You probably, you may remember him.
He had a viral prank back in the day when Elon bought X. Him and his buddy pretended to be fired X workers and they went outside with their boxes and gave all these like press interviews about how Elon was firing them for these ridiculous reasons and all these crazy things Elon was doing. It was kind of this like viral moment. And of course, they're just like random people that just showed up at the Twitter headquarters the day Elon was taking over and just had like boxes.
And so it's kind of funny. So he went viral for that. But he's also an actual founder who starts actual, you know, was starting an actual company. So what's interesting is this $10 million round, it's a whole bunch of really big VCs that are backing this.
It's not random people. It's Bessemer Ventures is leading the round. Horizon VC, 8VC, Y Combinator. Of course, the CEO of Vercel, which is Guillaume Rauch.
The Twilio co-founder, Jeff Lawson. The CEO of Perplexity, Arvind Srimvoss. So a whole bunch of high-profile players. And what's interesting is a lot of people, I think they kind of laughed at this company saying like, look, your company's going to be completely killed by the latest updates of, you know, better and better models from ChatGPT because you're a data analyst.
Well, ChatGPT can analyze data too and it can make you graphs. Kind of do everything that you guys are doing. So why are you special? Now, you're just a wraparound ChatGPT.
They're going to roll over you. Like, how could you compete? Why are you special? I think this is a really important question that a lot of AI companies are getting asked right now.
But I think that the ability to go deep on one specific topic and one specific dimension, one specific industry or niche is so valuable that these big foundation models will never be able to get every single feature set and tool that a person in any specific industry would need. They can generally make tools that are useful for everyone. But when it comes to, you know, every little thing that a welder needs to do and every, you know, maybe software or use case that you could think of, you just want like a welder-specific software tool or a salesperson-specific software tool instead of just going on ChatGP for anything. So in any case, what are they doing?
The founder is Raul Sunwalker. He actually launched the company back in 2022. He went to Y Combinator for it. But what's interesting is it was originally a logistics startup and they pivoted away from that.
Again, I'm a big fan of the pivot. If your company isn't working, don't scrap it. You built a lot just to find new ways to grow and complete different concepts. It was basically designed to act like a data scientist, analyze, and then visualize data sets and it performed predictive modeling.
It was basically running from ChatGPT and Claude and Gemini, which is interesting. I love the ability to swap between the three models because there's always a new, whatever the model that came up most recently is always the best. So if you always want the best, if you just use ChatGPT for everything, while when models come out that are better, you're going to be stuck with something that's not the best. Whereas if you have all these platforms that just allows you to switch to the best model, honestly, I think there's a huge value in startups that are doing that.
The competition from the top models makes startups more viable, in my opinion. But basically, they carved out their own niche and they said that they have about 2 million users and they have more than 10 million visualizations, data visualizations that have been generated. So this is something that's very popular. A lot of people are using it.
They said, quote, the easiest way to use Julius is to just talk to it. You can talk to AI like you would talk to an analyst on your team and the AI, like a human, would go run the code and do the analysis for you, right? So you kind of have to know what you're asking for, but I think they help a lot of the tools that make that easier than just straight using ChatGPT. Something that you could possibly ask it would be, can you visualize how revenue and net income correlates in different industries in China versus the US?
And we'll be able to talk about something for you to visualize that. What's interesting is last year, a professor at Harvard Business School, Ivan Bojivanov, he was really impressed. He actually saw it and he asked them to modify it to be specifically for Harvard's new required courses called Data Science and AI for Leaders. So it's kind of interesting.
I think those kinds of projects help a product along immensely, right? If someone's like, you know, we have a specific use case. In this case, it's literally a class for Data Science and AI and Leaders. So they have a very specific Data Science class and they're like, we need to be able to do all these things.
And so it's cool when you partner with academic institutions or businesses, you can also do this like a business partnership and they tell you the features that specifically they need in order to accomplish the task. You're making your product so much better. So I think this is a kind of good collaboration they did with Harvard and I think it helped out the product a lot. So one thing that Swan Walker said about this, he said, people told us you're not going to succeed basically because ChatGPT is building this.
What we found was that being focused on a use case is really important. So of course, he kind of got a little notoriety from his viral prank back in the day, but he turned this into a real company, really focused on a use case. And so I think that overall, this is a really interesting company and a huge congratulations to the whole team on raising $10 million pre-seed round. I'm excited and curious to follow along in the company to see how it grows from here because it's reached a decent amount of growth with 2 million users, but I'd be curious to see how they scale beyond this.
All right. Thank you so much for tuning into the podcast. I hope this was interesting and kind of got your mind thinking a little bit about how companies can be super viable today, even if the quote unquote AI GPT wrapper by going really deep on a specific industry and solving a problem for a specific user base and user set. If you learn anything new, I would love a rating and review on the podcast.
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You don't have to pay $20 subscriptions to a hundred different platforms. Just go check out AIbox.ai and I hope you have a fantastic rest of your day.