Tim Hwang
Analyst · ROTH MKM. Your line is open.
Yes. Yes. So, the way we think about it is two fronts, right? So, can we automate some of the things that we’re doing already within our operating expenses using AI? And so there are areas, for instance, in customer acquisition or in data acquisition, things like that, where we’re retooling some of our internal kind of capabilities. Specifically within R&D, I think that we have seen our market leadership extend ourselves largely because of the partnerships we’ve executed with OpenAI’s ChatGPT, Google Bard, Microsoft Bing, and so on and so forth. And those things sort of enable us to be able to reduce our R&D expenses by sharing the load with these large-language models and the like. And so, that’s why you’re seeing this reduction in R&D expense relative to operating expenses. Now, those are also obviously nice to have some things and obviously drive some level of profitability. But at the end of the day, we need to build a great business, and a great business is determined by having a great product. And so, for us, that – you can sort of see that in, for instance, the launch of FiscalNoteGPT, where we’re combining all of our data, the decade-long investment that we have in legal and regulatory information, and then the ability to be able to kind of combine that with our own language models to be able to create things like question-and-answer systems, summarization capabilities, and other things that are unlocking new capabilities overall. So, it is this combination of sort of reducing operating expenses and also creating new capabilities that I think are just unparalleled in terms of the ability to be able to create these types of capabilities overall.