SaaS Interviews with CEOs, Startups, Founders
Deep Tech Founder Lands First Customer at $150,000 per year
12 May 2022
Chapter 1: What is the main topic discussed in this episode?
What are these companies paying on average per month or per year to use your technology?
So now we have the first customer, it is like 130K for the annual contract.
You are listening to Conversations with Nathan Latka, where I sit down and interview the top SaaS founders, like Eric Wan from Zoom. If you'd like to subscribe, go to getlatka.com.
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Chapter 2: What is the significance of landing the first customer for a startup?
It's like a big Excel sheet for all of these podcast interviews. Check it out right now at getlatka.com. Dr. Yuchun Zong has been passionate about AI since the start of his PhD university in Edinburgh back in 2010. Since the first year of his PhD, he started to publish several papers on Boltzmann machines and approximate interference in one of the most influential AI conferences near IPS.
His research contributes to the core of his current company, Boltzbit AI at boltzbit.com. Dr. Yuchun, you ready to take us to the top?
Yes.
Okay. So BoldSpit's tagline is make AI accessible to everyone. What does that mean?
So it means to really give people who have the data the power of AI so people can just develop AI from their data without having knowledge of machine learning or deep learning. And who are these people?
I mean, who are you selling to?
Selling to its business. Yes. Mainly it's business and particularly for a lot of companies who have a lot of customer data and product data and you want to make automated decisions like product recommendations and user search, answer a lot of decision questions.
And what are these companies paying on average per month or per year to use your technology?
So now we have the first customer, it is like 150K for the annual contract, right? But our main business model, it is kind of like pay as you use. It's kind of cloud-based SaaS. The model is basically based on how much data you upload on our platform and you train the model and then you pay as the computational hours.
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Chapter 3: How does Boltzbit AI make AI accessible to businesses?
And you said the run last year was for 1.6 million?
Yes.
1.6 million. Okay. And how did you, was that a, did you come up with a valuation for that or was that a convertible note with no cap?
No, that is a VC investment. That is, yeah, it is not loan. Yes.
Most people when they're raising their seed round are selling between, you know, 15 and 20% of their business. Is that what you did?
Um, yeah, roughly. Yeah.
Okay. So that means you raised it like a 10 or $12 million valuation, something like that.
Uh, yeah.
Okay. Was that fair? Do you think that was a good valuation or bad valuation?
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Chapter 4: What pricing model does Boltzbit AI use for its services?
broke a $540 million valuation last year, and he spends zero time on technical onboarding for new hires. He relies on Electric IT support to onboard 10 to 20 new teammates per quarter. Now, Electric is best fit for US-based companies with between 15 and 500 employees. They reached out and said, Nathan, we love your audience. We love SaaS. Can we put Electric in front of them? And I said, yes.
So check them out today. at nathanlatka.com forward slash electric. And as you guys know, in Latka style, I said, you gotta sweeten the deal. So they said, Nathan, for your folks, just for taking a meeting, they'll get a free pair of Beats Studio Buds. Now I looked up these buds on Amazon, it's $120 value.
So to get those buds, again, just for taking a meeting, go visit nathanlatka.com forward slash electric today. That's nathanlatka.com forward slash electric. What is that use case, this first use case you're building?
Yeah, it is for search engine technology. So basically use Generate TBI to automatically pass different type of documents. Not only text image can be mixed and then combine those information together, allow user to interactive search. So you're not just giving an image, you can even highlight which part of the image that is using this most relevant. And this is something special we developed.
Did you have to buy a very large data set to feed your initial sort of panel data set to grow your algorithms, your AI, et cetera? Where did you get the initial data set to train your models on?
The initial data set, this is a good thing of generative AI because it can learn on the data itself. So we use a lot of public data set. And you know, a lot of generative AI trained on very public data sets.
Like what? Can you name a few of those data sets?
Like one of these, like Cocoa and ImageNet. A lot of public data that you can find on GitHub.
Interesting. Very cool. Okay. So nine people hold time on the team today. Are you raising capital right now?
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