In the competitive Dallas–Fort Worth real estate market, agent teams constantly seek ways to maximize productivity. Justin Nimergood, founder of the Top Gun Team at Epique Realty in Southlake, TX, has identified a persistent inefficiency: cold calling. Traditional coaching often emphasizes consistent phone outreach, but Nimergood argues that time spent dialing unresponsive contacts is time stolen from revenue-producing tasks.
Nimergood’s framework focuses on what he calls commission-generating activities (CGAs)—showings, negotiations, client consultations, and follow-up with warm prospects. Cold outreach, he says, does not qualify. “When a lead is cold, they need to be warmed up again before we’re going to be able to have any real effect on them,” he explains. An hour or two spent on cold calls could instead advance deals already in motion.
To solve this, Top Gun Team partnered with Angel AI, a company providing an AI-supported call center staffed by human callers based in Dallas–Fort Worth. The process begins with the team submitting a call list and script. Before calls are made, Angel AI’s “responsive AI” scans publicly available data—including production records and online activity—to rank contacts by priority. The most promising prospects are called first and most frequently. After calls, the AI analyzes recordings for buying signals and generates a report identifying genuinely interested contacts.
Nimergood describes the outcome: of 100 people called, perhaps 10 answer, and of those, the system flags five as priority leads based on conversational cues. Agents receive this filtered list instead of raw call logs. The reporting layer is the most operationally valuable part, he says, as it automates the triage process, allowing agents to focus personal outreach on already-engaged contacts.
Beyond warming leads, the system also removes dead ones. When AI analysis indicates a prospect is no longer in the market, the contact is archived rather than recycled. “It lets us know if they’re no longer in the market for a home or whatnot,” Nimergood says. “Then we take them out of our funnel, or we archive them. The point is, we don’t waste our time with initiatives that are not productive.” This reduces the signal-to-noise ratio in a team’s pipeline, eliminating stale leads that consume resources.
Nimergood emphasizes the importance of domestic, human callers. While fully automated AI voice calling exists, he believes it’s not ready for scale: “I think that will have a place, and that does have a place in our industry, but not quite yet. It hasn’t been ironed out or perfected yet.” He also notes that international outsourcing carries a perception problem—”People stereotype. They just do, and so the more we can minimize that, the better.” The domestic model threads the needle between full automation and in-house calling, addressing both reputational risk and opportunity cost.
This approach illustrates how agent teams are treating outreach infrastructure as a distinct operational layer. Nimergood applies the same principle broadly: agents focus on CGAs while support systems handle lower-value tasks. “If they want to be top-producing agents, they have to minimize their administrative time, and they have to maximize their CGA time,” he says. For teams scaling up, the ability to process large lead volumes without burdening agents determines whether more leads translate into more closed deals or just more unanswered calls.
As the real estate industry evolves, the integration of AI-prioritized call centers may become a standard tool for high-performing teams seeking efficiency. Nimergood’s model offers a glimpse into how technology can support—not replace—the human element in sales, ensuring agents spend their time where it matters most.
