In some cases, pivoting can be the wisest decision for company leaders. Watch Netflix's transformation from DVD to streaming or Corning's transformation from light bulbs to touchscreens.
The list of highly successful startup pivots goes on. And more. And more.
A less obvious (but by no means unsuccessful) pivot is Numa's. The co-founders scrapped the startup's original conversational AI product and sold customer service automation tools instead. But it's more than just a tool. These tools are aimed at car dealers.
Numa CEO Tasso Roumeliotis says it sounds like a very specific niche, but it's profitable. The company closed a $32 million Series B round in September.
“We were early builders of AI and conversational commerce,” Roumeliotis told TechCrunch in an interview. “But after seeing a huge opportunity in the automotive industry, we decided to focus our AI entirely on the automotive industry.”
Roumeliotis co-founded Numa in 2017 with Andy Ruff, Joel Grossman, and Steven Ginn. Grossman comes from Microsoft, where he helped ship major products like Windows XP and lesser-known products like MSN Explorer. Ruff, also a Microsoft veteran, led the team that created the first Outlook for Mac client.
In fact, Numa is the co-founders' second business. Roumeliotis, Grosman, Ginn and Ruff previously founded Location Labs, a family-friendly security company that AVG acquired for $220 million a decade ago.
Roumeliotis said what brought together the old staff behind Numa was a shared belief that “thoughtfully applied” AI could transform entire industries. “The market is full of AI and automation point solutions or a wide range of tools that are not focused,” he said. “Numa provides an end-to-end solution that prioritizes the needs of our automotive dealership customers.”
There are more than 17,000 new car dealerships in the United States, representing a $1.2 trillion industry. However, many dealerships struggle to manage customer service requests. According to one study, one-third of dealers miss at least one-fifth of the calls they receive.
Poor responsiveness will result in poor customer service scores, which in turn will negatively impact sales. But Roumeliotis argues that Numa can prevent things from getting that bad by addressing low-hanging fruit.
Image credit: Numa
Numa uses AI to automate tasks such as “rescuing” missed calls and booking services. For example, if a customer calls a dealership but hangs up shortly after, Numa can send a follow-up text or automatically place a reminder call. The platform can also provide customers with ongoing service status updates and facilitate trade-ins by gathering the necessary information upfront.
“Many dealerships still rely on legacy systems that are inefficient and lack integration with modern AI-driven platforms,” Roumeliotis says. “Today's consumers expect fast, seamless interactions across all platforms. Dealers are struggling to meet these expectations, especially in areas such as real-time communications, service updates, and personalized experiences. AI can help address this.”
Other small automation vendors (such as Brooke and Stella AI) offer products designed to ease customer service burdens for dealerships. Meanwhile, tech giants sell a variety of generic solutions for automating customer service. But Roumeliotis insists that Numa stands out because it understands how workflow within a dealership impacts the end-customer experience.
“Dealership service leaders and employees are constantly on the go, working directly with customers, going out to check on cars and parts, answering ringing phones, and coordinating coordination with co-workers. ,” said Roumeliotis. “Numa brings all of this together in a way that we intentionally designed the AI and the users within the dealership to drive the platform’s behavior rather than the other way around.”
Roumeliotis argues that Numa also has other benefits in its in-house model, which drives platform automation. He said the model was trained on datasets from OEM and dealer systems, as well as conversation data between dealers and customers.
Have each of these clients, OEMs, and distributors been notified that their data will be used to train Numa's models? Roumeliotis declined to say. “Numa's model is bootstrapped by a feedback loop between dealers, customers interacting with dealers, and the use of Numa to facilitate this,” he said.
Image credit: Numa
The answer probably won't satisfy those who value privacy, but it doesn't seem to matter to many dealers. Numa has 600 customers in the United States and Canada, including some of the world's largest automotive retailers. Roumeliotis claims Numa is “almost” breaking even on cash flow.
“We don't need capital to continue growing our revenue,” he added. “Instead, Numa is using the funding to accelerate product development by expanding its team of AI and machine learning engineers, including investing in building AI models for the automotive industry.”Currently. The company has 70 employees.
Paying dividends in Numa's conquest is dealers' willingness to experiment with AI to abstract certain back-office tasks.
According to a study last year by CDK Global, an automotive software provider, 67% of dealerships are using AI to identify sales leads, and 63% have implemented AI in their services. Those polled were extremely bullish on technology overall, with nearly two-thirds saying they expected positive returns.
Touring Capital and Japanese conglomerate Mitsui & Co., one of the major shareholders of automaker Penske, led Numa's Series B round. Costanoa Ventures, Threshold Ventures, and Google's AI-focused venture fund Gradient also participated in the round. The funding brings Oakland-based Numa's total raised to $48 million.