The Top Gun Team, a high-performing real estate team in Southlake, Texas, is shifting how agent teams handle cold outreach. Founder Justin Nimergood argues that traditional cold calling is one of the most persistent inefficiencies in the industry, pulling licensed agents away from tasks that actually close deals. His solution: outsource cold calling to an AI-supported call center that filters leads before agents ever pick up the phone.
Nimergood's framework centers on what he calls commission-generating activities (CGAs), which include showings, negotiations, client consultations, and follow-up 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. Even rapid-fire dialing through 100 contacts takes one to two hours, time that could be spent on work that moves deals forward.
The Top Gun Team has partnered with Angel AI, which provides an AI-supported call center staffed by human callers based in Dallas–Fort Worth. The model works by having Nimergood's team submit a call list and script, and the call center handles the outreach. What distinguishes the service 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 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, the system identifies five as priority leads based on conversational cues. Agents receive this filtered list rather than sorting through raw call logs. The reporting layer is what Nimergood considers 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 or whatnot. 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,” says Nimergood. This improves the signal-to-noise ratio in a team's pipeline, ensuring agents inherit a smaller, more accurate list.
Nimergood is deliberate about one aspect: the callers are human and based in Texas. He acknowledges fully automated AI voice calling exists 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. It hasn’t been ironed out or perfected yet.” He also notes that international call centers introduce a perception problem. “People stereotype. They just do, and so the more we can minimize that, the better.”
This domestic, human-caller model threads a needle between full automation and in-house calling. For teams scaling quickly and managing large databases, this middle-ground approach addresses 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. 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 more leads translates into more closed deals, or just more unanswered calls piling up in an agent's queue.
