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it's not clear why Stripe would care about that. And I don't think it's a great fit
I don't see how this doesn't just compress to zero. This is just this, this process business is a common business model and they almost always go to zero over time. That being said, J. Cal brought up a really good point, which is the data is the actual valuable thing. And it's not clear why Stripe would care about that. And I don't think it's a great fit, but for somebody specifically, somebody like an Apple or maybe a meta that hasn't been able to really build out their AI capabilities, this co
I think there's a chance that we're underestimating the power of Google's ad network right now. It's quite possible that knowing your queries in Gemini, knowing what you're doing in calendar, knowing what you're watching on YouTube could lead to a stream of more target ads that do better and are more valuable. And so we've been seeing a number of companies, startups, you know, in the early stages and year one startups that are figuring out how to use your queries and what you're doing in AI to p
And I use Gemini and I have a sort of AI first company where everybody's required to do their work on AI two or three different Claude, Gemini, Grok, etc. And what I've been noticing inside these products is they're very deeply integrated. I got surprised just the other day. I was asking it about a travel question and it referenced my G calendar. I didn't know they could do that. Then, obviously, you can use Gemini inside of Google Docs and they have four or five products right now that are one
And if they cut their team size down, earnings are going to go massively up and they're spending 75 billion dollars on infrastructure.
I think they're going to cut a large number of employees, get people to return back to office and take this a little more seriously on a corporate level because you got that sense from Sergey who's in the office every day.
Everyone and their mothers competing in this space. But what makes us different is we have a platform solution. So those three components that I mentioned, we have the decentralized indexer, we have the on-prem LLM, and then the response control. So I want you to focus on those three components as our differentiator between our other competitors, right? So a lot of those names are going to be very large and the ones that you would expect. But our solution, I think, for the types of customers tha
We charge a monthly subscription of $10,000 to $20,000 per month and a one-time installation fee of $250,000 to $350,000.
This is a breakdown of our monthly revenue. I mentioned the $125,000. That's down here. That's our recurring revenue. And then we have non-recurring revenue of about $1.2 million for a total of $2.1 million.
we have 125,000 in monthly revenue and nine enterprise clients.
The problem is regulated industries want LLMs, but cloud solutions are too risky. So think about banks, insurers, and credit unions. They want their language models that are completely under their control. That's where Abacus comes in. It's the first on-prem AI assistant built for regulated industries.
because you have open source open ai and just major players building these models the models are going to be coming down to zero uh and then it is a game of data and features and focus around the customer experience which i think open you see in what open ai is doing right now their last announcement for the omni uh last week was really focused around user experience and the product itself
i think that what slack probably saw ... was as david said just um you know a level of sophistication and scale and ability to cross sell and upsell that was needed for enterprise scale