Symone Graham
Dec 1, 2025
RevTech Labs has spent more than a decade positioning Charlotte as a proving ground for emerging financial technology. But Dan Roselli, the local accelerator’s co-founder and managing director, saw the real shift arrive long before generative artificial intelligence made headlines.
RevTech Labs has spent more than a decade positioning Charlotte as a proving ground for emerging financial technology. But Dan Roselli, the local accelerator’s co-founder and managing director, saw the real shift arrive long before generative artificial intelligence made headlines.
Early-stage founders at the organization he helped build experimented with AI-adjacent tools years ago, including real-time coaching engines and early language-model applications. That vantage point gave Roselli a front-row seat to how quickly and unevenly the technology reshapes financial services, compliance workflows and startup strategy.
Today, AI is embedded across RevTech Labs’ deal flow and its curriculum. Nearly 70% of 2024 applicants tied their value proposition to AI. This prompted the accelerator to evolve how it vets companies, assesses pitch decks and distinguishes between genuine innovation and what Roselli calls “AI faking it.”
The shift builds on his long track record of cultivating Charlotte’s fintech scene. He founded startup incubator Packard Place in 2010 and scaled the accelerator, launched in 2012, into a national draw for founders navigating heavily regulated industries.
Roselli sees the promise and the pressure. Banks adopt AI faster than expected. Investors flood the sector. Questions about ethical training and data have moved to the forefront. At the same time, he argues AI may most transform lean startup teams and accelerator operators. It unlocks faster market entry and new forms of mentorship and evaluation.
For Roselli, AI is no longer optional. He says it is becoming the foundation for the next wave of financial innovation.
Roselli recently spoke with CBJ about how AI is reshaping RevTech Labs’ accelerator model, what he’s seeing from fintech founders adopting the technology and how Charlotte’s expanding tech ecosystem is positioning the region to lead in the next wave of AI-driven financial innovation. Following is a transcript of that interview, edited for length and clarity:
How is RevTech Labs integrating artificial intelligence across its accelerator programs, and what advantages are you seeing in how startups use AI to scale more efficiently?
One of the interesting things about RevTech Labs, because we are an accelerator, we see trends maybe a little earlier than other people in business see them, because it’s the people that are starting companies and trying to disrupt the status quo. We saw a big surge in AI, even before ChatGPT really kind of put it on the mainstream. And there’s also some precursors, I would say, or sister technologies to AI, like large language modeling. We had some people even eight years ago, using Watson from IBM as a way of, in real time, giving feedback to sales agents based on how the conversation was going. Everyone thinks it just kind of jumped onto the universe with ChatGPT. But the reality is, the technology has been building for quite some time.
Many of your portfolio companies operate in highly regulated industries like banking and health care. How do you guide founders to balance innovation in AI with compliance and responsible data use?
AI is an incredibly powerful tool for banks and financial services and insurance companies because of the complexity of compliance. AI has the ability to be more efficient and more accurate than humans. Its ability, for example, to detect fraud or irregular transactions, is significantly better than a human trying to do the same. And so there are some real positives to that technology for large companies. I’m actually kind of surprised, if you looked at some of the big financial services organizations, how quickly they have at least put their toe in the water with AI-driven chat bots for interaction. They certainly did it from the use of AI in compliance and regulatory fraud. We see that as just a huge area that has exploded in the last 18 months, and banks are interested in doing that. I think where there’s some concern, especially in the financial services and insurtech space, is how AI is being trained, and what data they’re trained on.
One of the most common questions our fintech founders get is, “How have you trained your model?” A lot of them have pivoted to building models within a firewall system. We don’t have one with Bank of America, but for example, they would take Bank of America’s customer data, and that model would be trained solely on data that BofA has the rights to use and where consumers have opted into and would not be used with any other client, and vice versa. And I think that’s the trend we’re going to see going forward is third-party tools, where a large fortune 500 company does not know how it’s been trained and it’s a black box to them, is not going to work.
How has AI influenced RevTech Labs’ own operations, from startup selection and mentorship to the way you measure growth or predict portfolio performance?
It certainly impacted the types of companies that are applying. In 2024 we had almost 1,000 companies formally applied to come into our program, and we took 25. A hyper competitive process, I would say over half, maybe close to 70% of those companies had an AI component driving their value proposition. So it’s certainly the number of companies out there and our interest in them has changed. I think that AI is one of those once in a generation, revolutionary technologies that you have to be aware of and have to adjust the way you’re looking at companies.
Having said that, I will say that there are still companies out there that will throw the AI name around, and they are not AI companies, and so there is a little bit of BS meter that we need to apply when we’re talking with founders. And it’s interesting when you ask a founder to explain in some level of detail how AI is driving their core value proposition. Some of them struggle to do that. And they’ll talk about a large language model, or they’ll talk about algorithms, but algorithms, per se, are not AI, and it’s much broader than that. You can tell of the founders that are kind of AI faking it.
Charlotte has become a hub for fintech and emerging tech innovation. What role do you see AI playing in strengthening that ecosystem, and how is RevTech Labs helping shape the city’s leadership in this area?
It’s interesting. UNC Charlotte just launched an AI program. They have an AI Ph.D. program as well. And I think I’ll give some shout outs to UNC Charlotte. Because they’re a university that is still emerging in many ways. They just reached tier one, r1 research university status. They don’t have a bunch of legacy research, and they have the ability to move quicker and react quicker to new spaces. I think they’ve done a really nice job of that with AI.
So I think our university system is one area where we’ve tried to partner very closely with the university. I think the secondary area is the large company connections that we have through our program. We have almost 500 mentors from 250 different companies. That’s just an immensely wide mentor ecosystem, and one of the main reasons why founders will come into our program is the ability to vet across a wide cross section of industry. The value proposition and others using the model, whether that will work in corporations. That depth and breadth of corporate connections is really at the core of why founders come into RevTech Labs.
The last thing I’ll say is kind of like a lot of emerging technology that was hot. I still argue there are very few companies that are truly AI companies, meaning their core of what they do is AI. ChatGPT would be an example. Open AI would be an example. Most of the fintech and insurtech startups are actually still insurance compliance platforms that use AI as an enabling technology to be more accurate and more efficient. We caution our founders in the fintech and insurtech space from labeling themselves an AI company versus labeling themselves as the four of the problems they’re solving, which is AI enabled.