In the competitive world of real estate, the traditional advice to agents is to spend hours on the phone dialing cold contacts to build a pipeline. However, Justin Nimergood, founder and leader of the Top Gun Team at Epique Realty in Southlake, TX, challenges this notion. He argues that cold calling is one of the most persistent inefficiencies in agent teams, pulling agents away from what he calls commission-generating activities (CGAs) — tasks that directly produce closed deals, such as showings, negotiations, and client consultations.
“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,” Nimergood says. The time spent on cold outreach could be better used on work that moves deals forward. For a team aiming to scale, every hour an agent spends on cold calls compounds into missed opportunities elsewhere.
To address this, Top Gun Team has partnered with Angel AI, a company providing an AI-supported call center staffed by human callers based in Dallas–Fort Worth. The model works by having the team submit a call list and a script, and the call center handles the outreach. What sets this service apart is a layer of “responsive AI” built into the process. Before calls are made, the 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 recorded conversations 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, the system identifies five as priority leads based on conversational cues. Agents receive this filtered list rather than sorting through raw call logs themselves. The reporting layer is the most operationally valuable part, as it surfaces information automatically, allowing agents to focus personal outreach on contacts who have already demonstrated engagement.
The call center model also removes contacts from the pipeline entirely. When AI analysis indicates a prospect is no longer in the market, that contact is archived rather than recycled. “It lets us know if they’re no longer in the market for a home,” 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 improves the signal-to-noise ratio in the team’s pipeline, giving agents a smaller, more accurate list rather than a bloated database full of dead numbers.
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 have a place eventually, but says the technology isn’t ready for deployment at scale. “I think that will have a place, but not quite yet,” he says. He also notes that outsourcing to international call centers introduces a perception problem. “People stereotype. They just do, and so the more we can minimize that, the better.” The domestic, human-caller model threads a needle between full automation and in-house agent calling, addressing both reputational risk and opportunity cost.
Top Gun Team’s use of Angel AI illustrates how agent teams are beginning to treat outreach infrastructure as a distinct operational layer, separate from the work agents do once a lead is warm. Nimergood applies this 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 managing growing lead volumes, the ability to process and triage large numbers of contacts without burdening agents determines whether adding more leads translates into more closed deals or just more unanswered calls.
