In the competitive real estate landscape of Dallas–Fort Worth, the Top Gun Team at Epique Realty is challenging conventional wisdom about cold calling. Founder Justin Nimergood argues that having licensed agents spend hours dialing unresponsive contacts is a persistent inefficiency. Instead, his team has adopted a hybrid model that combines human callers with AI-driven prioritization, aiming to optimize agent time and improve pipeline quality.
Nimergood's framework centers on what he calls commission-generating activities (CGAs)—tasks that directly produce closed deals, such as showings, negotiations, and follow-ups with warm prospects. Cold outreach, he says, does not belong on that list. “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. Rapid-fire dialing through 100 contacts can consume one to two hours, time that could be spent on activities that move deals forward. For a scaling team, every hour spent on cold outreach compounds into missed opportunities.
The Top Gun Team has partnered with Angel AI, an AI-supported call center staffed by human callers in the Dallas–Fort Worth area. The process begins when Nimergood's team submits a call list and script. Before calls are placed, 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 which contacts showed genuine interest. Nimergood describes the output: of 100 people called, perhaps 10 answer, and of those, five are flagged as priority leads based on conversational cues. Agents receive this filtered list instead of sorting through raw call logs.
The reporting layer is what Nimergood considers most operationally valuable. The system automatically surfaces which cold contacts to prioritize, allowing agents to focus personal outreach on those who have already demonstrated engagement. Moreover, the call center model removes contacts from the pipeline entirely when AI analysis indicates they are no longer in the market. “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 approach helps teams manage large databases by eliminating stale leads, improving the signal-to-noise ratio.
Nimergood is deliberate about one aspect: the callers are human and based in Texas. He acknowledges that fully automated AI voice calling exists and may eventually have a place, but says the technology is not ready for scale. “I think that will have a place, and that does have a place in our industry, but not quite yet,” he notes. He also points out that international call centers can create perception problems: “People stereotype. They just do, and so the more we can minimize that, the better.” The domestic, human-caller model balances full automation and in-house agent calling, addressing both reputational risk and opportunity cost.
This strategy illustrates how agent teams are beginning to treat outreach infrastructure as a distinct operational layer. Nimergood applies the same principle to his team's broader operations: 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 managing growing lead volumes, the ability to process and triage large numbers of contacts without burdening agents determines whether adding leads translates into more closed deals or just more unanswered calls. By leveraging AI-prioritized call centers, the Top Gun Team aims to ensure that every agent hour is spent on activities that drive revenue.
