Transcript

Yeah. So we, uh, just raised $41 million in C plus Series A. Alright, there we go. Congratulations. Very exciting. Alright, explain to me how this plugs in. Obviously there's a lot of folks that have an accounting layer of record, a single pane of glass and ERP and accounting suite. Do you want to just plug into that? Do you want to RIP and replace that? There's so many different folks eating around the edges creating different solutions. I don't think anyone knows exactly how the market will play out, but what have you built? Yep. So we built a system of action and system of intelligence which works with any system of record. OK, so when you go to an enterprise company asking them to replace Arps, like asking them to do brain surgery, I was approved and I would not agree to that. And we say that, hey, your system of record is where your data should eventually sit. We do the we help with automating the human work of grabbing the data from upstream system and then eventually finding anomalies. Matters. I don't know if you're following, but last year was the maximum number of companies in the US which had material misstatements and like up to 40% stock drops. Most mistakes from accounting specifically last year. That's not good. Well, give me some examples of where the current crop of AI models really excels in finding these types of problems. And then where do you want to still leave the human in the loop? Yeah. Look, I'll just out of saying our problem are we are not going after the human labor salary. We are going after errors in efficiency and pain that I personally face both as an auditor and and and as an accountant for 20 years. Yeah, they are not enough accountants in the world that you can truly hire for the amount of work that's there. So in terms of where AIS are very good at today, they are very good at taking. A defined set of instructions and following things over and over again for variety of transactions, provided you give them a deterministic operators which we have built that they will only use those tools and then come up with the right answer. So we are using this hybrid approach where agents follow Maxima tools to come up with the exact same answer. And so when Deloitte and UI comes knocking, looking at the work that Maxima produced, they will they will do 2 + 5 and the answer will always be 7. It will not just be 15. So that's one thing we determined really well. Second is it's, uh, the really good at finding anomalous behaviors and errors that might happen because it is. It's looking at millions of transactions over time within the company. It can just see that, hey, this, your legal bill used to be $50,000. Suddenly it's $500,000. Turns out Jim, Jim had a late night and he had one extra 0 and that's why it went up.