Last week, Naborforce, a Richmond, Virginia-based startup aimed at helping seniors age in place, expanded operations into Charlotte.
The startup was founded in 2018 by Paige Wilson to connect aging adults to a network of "Nabors" for social engagement and on-demand support with errands, transportation and help around the house. She said the expansion into the Charlotte region is the startup's biggest push yet outside of Richmond.
"It gets easier in every successive market as we’re continuing to learn and grow," she said. "From the time we launched, no one has questioned the demand for this, so it’s really a matter of execution. Charlotte being larger than Richmond, I think it’ll be a very good market for us."
The startup launched a new service offering last month that will help employers better support workers who are assisting with the care of an older family member.
That program, called Naborforce for Laborforce, will provide resources and backup eldercare benefits designed to help employees balance work and caregiving, while boosting productivity and reducing turnover, Wilson said.
Two Richmond institutions have already adopted the program, and Wilson said the Naborforce team is already working on securing companies in the Queen City.
"We’re in discussions with a very large financial institution in Charlotte," she said. "They’ve been very public about (the need) and did a study themselves on why this is important."
In addition to Richmond and Charlotte, Naborforce services are available in Charlottesville, Virginia; Bethesda, Maryland; and the Raleigh-Durham region. The startup raised a $2 million seed round in June, led by Nashville, Tennessee-based Claritas Capital Partners.
The Naborforce team went from three employees to 11 over the last 12 months, and as it continues to grow, Wilson said she plans to begin looking outside the current coverage area.
"For now, we’re kind of sticking close to home ... but I expect that pretty quickly into next year we’ll move out of the mid-Atlantic region," she said. "We wanted to make sure we could continue to prove out our model so we could execute well."