#StartupsEverywhere: Durham, N.C.

#StartupsEverywhere: Lauren McCullough, CEO and Co-Founder, Tromml

This profile is part of #StartupsEverywhere, an ongoing series highlighting startup leaders in ecosystems across the country. This interview has been edited for length, content, and clarity.

Revving Up Sales Insights with AI Technology

With a background in economic development and a startup itch, Lauren McCullough co-founded Tromml, helping the automotive industry understand sales dates. We sat down with her to discuss her company, the role of open source in AI, navigating intellectual property rights, and more.

Tell us about your background. What led you to Tromml?

I entered entrepreneurship through more of the economic development perspective. My first job out of college was working at a business incubator in rural southeast Ohio with a fund the state put aside with money to invest in equity and non-dilutive funding for technology businesses. After spending a couple of years there, I moved down to Durham, N.C. looking for more of a thriving entrepreneurship scene. There, I ran a program that gave non-dilutive funding to founders called NC Idea. 

After working in the economic development space, I was ready to work on the other side of the table. I spent some time doing fractional work for startups focused on early-stage company growth, where I stumbled into my current vertical—the automotive aftermarket industry. From there I worked full-time for a startup doing automation, where I met my current co-founder.

What is the work you all are doing at Tromml? 

Tromml was started because we noticed that trends in digitization for commerce weren’t translating to the automotive industry and auto parts. Organizations have a massive amount of data, but they don’t have enough analysts to assess it. We started trying to make sense of the data for profitability and margins but eventually shifted into automated sales analysis in general.

The name Tromml comes from trommel, the equipment used in gold mining that separates all the dirt from the nuggets of gold. With that metaphor in mind, we are trying to help our customers find gold nuggets of information within their data. We can plug data into our AI models to get a data story, understand trigger events, and provide insights. 

At this point, we are mostly using open-source models. We build our own data models to get the information that we put into our data pipelines, into what we would consider to be an AI-ready place where we can deploy a trained Large Language Model (LLM) tool to put that data into context.

You mentioned using open-source models and AI tools to build your software. What do you want policymakers to know about the role of open source in the startup ecosystem?

Without open-source models and tools when we started, we would have been years behind on deployment. No one is building an LLM from scratch when open-source models provide a foundation to build upon. The real innovation comes from how these models are fine-tuned and applied to specific industries. It’s like hiring an intern straight out of college—they come with a basic skill set but require training to become invaluable over time. AI works the same way—it’s a resource that grows more valuable as it’s trained. These tools are crucial for startups, enabling us to adapt, innovate, and bring solutions to market faster.

Are you pursuing any patents for your product? If so, what has that process been like for you and what are your concerns? 

As a team, we are actively discussing whether to pursue the patent process or keep our innovation as a trade secret. A significant concern is that filing a patent obligates us to defend it against potential infringement claims by bad actors, which could divert already scarce capital toward costly litigation. Additionally, the time and expense involved in filing a patent are considerable. In the rapidly evolving world of AI, where growth is exponential, these challenges weigh heavily on our decision-making process. 

Are there any local, state, or federal startup issues that you think should receive more attention from policymakers?

The mess regarding R&D expenses is still looming. There is so much ambiguity that we don’t even know what’s gonna happen when we file. Right now that's not an extreme worry, but at some point we could have tax repercussions because of it. We’re trying to stay on top of everything, but the lack of clarification and changes is continuously confusing. 

Another interesting idea to improve the funding landscape for startups would be micro grants. When I worked in Ohio, the state had an investment fund specifically for early stage access to capital. 

There are so many innovative companies emerging from our community, yet there is no capital available to help them get started, particularly if the goal is to use entrepreneurship as a tool for economic mobility. Many aren’t aiming to build the next unicorn; they simply want to create a $10 million business they can eventually sell. Even that feels out of reach due to a lack of resources. 

Despite federal investments in entrepreneurship in places like North Carolina, we’ve seen none of that support. In addition to Tromml, I have another small business (led by two women). We've built a company that invests in our community, pays living wages, and prioritizes impact. Yet, despite following all the rules and doing everything by the book, we’ve received no assistance from either state or federal programs..not even affordable debt. 

What are your goals for Tromml moving forward?

This year will be a bit of a grind and we're trying to still be agile, build an infrastructure this year, and start to hit that venture-backable trajectory by the end of this year. 

Ultimately, our goal would be to sell down the line and get acquired by a strategic partner, where we feel like the company can maintain a brand and grow. Then we’d want to circulate that money back into the automotive ecosystem because they are the ones who have supported us.


All of the information in this profile was accurate at the date and time of publication.

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