DealGround, an AI-powered intelligence command center for commercial real estate professionals, is transforming the way brokers prospect for deals. According to Dan Mosher, CEO and co-founder, the platform now allows brokers to run the entire prospecting workflow—from identifying a target property to generating a customized cover letter—without leaving the system. This capability compresses a process that traditionally took days into minutes, with significant implications for broker productivity and deal volume.
The traditional approach to prospecting in commercial real estate is linear and tedious. A broker with a buyer interested in net lease properties, for example, would need to identify comparable properties, trace ownership through Secretary of State filings, find the individual behind the LLC, locate contact details, and then write personalized outreach. Each step lived in a separate system, making the process manual, slow, and prone to errors. "All of these were very manual, slow, and had lots of errors," Mosher said. "They were prone to human error. And a lot of the time, they might have missed deals because they didn't have the right name of the owner." The fragmentation meant that brokers who wanted to prospect at scale were either accepting a high error rate or spending an enormous amount of time on research that had nothing to do with negotiating or closing.
On DealGround, a broker who specializes in a specific tenant type can now run a filtered search across every property in a state with that tenant, pull a full list of owners who have not transacted in a set number of years, retrieve contact information for all of them, and then use the platform's AI to generate customized outreach letters for each one. "They could have ten or twenty different prospect property locations, and then they're creating twenty different customized cover letters based on the characteristics of that property," Mosher explained. "The ability to kind of use the whole system, soup to nuts, from ideation, identifying the building to an actual letter of a couple paragraphs that is pertinent to that owner, has been incredible to see." The personalization is not superficial. Because DealGround has the property and tenancy data, the outreach can reference specifics: the tenant, the market, the holding period, what a comparable sale looked like nearby. It reads like a broker who did their homework, because the platform did it for them.
Commercial real estate has always rewarded brokers who could prospect more consistently than their competitors. The limiting factor was never ambition; it was time. Writing twenty tailored letters by hand meant most brokers settled for a handful. With AI doing the heavy lifting on drafting, that ceiling disappears. "They're making more money by being creative about deals they want to bring to the table on behalf of their clients," Mosher said. "They're able to find deals they might not have otherwise found, and the time of research has dropped dramatically." The platform also cuts down on the deals that die before they start because a broker could not locate the right contact. With validated ownership data across more than 160 million properties, the blank spaces in a prospecting list shrink considerably.
What makes this prospecting shift meaningful is not just speed, it is coherence. When the property data, ownership data, contact data, and AI writing tools all live in one place, there are no handoffs between systems and no manual re-entry. The whole process has a logical flow: find the property, find the owner, reach out. Mosher described watching brokers exit their existing tool subscriptions after getting comfortable on DealGround. That is not a small thing in an industry where platform switching is historically slow. It suggests that when the workflow genuinely fits how brokers operate, adoption follows. For more information, visit www.dealground.com.
