Why Southlake's Top Gun Team Is Redefining What "Team Support" Means for Agents

Written by:

Heather Hook

Date:

04 Aug 2026

KeyCrew Studio

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Most real estate coaches teach that consistent phone outreach builds a productive pipeline. What they rarely address is the cost of having a licensed agent spend two hours dialing contacts who mostly don’t answer, time that produces no revenue and pulls agents away from work that does.

Justin Nimergood is the founder and leader of the Top Gun Team, a high-performance Dallas–Fort Worth real estate team at Epique Realty headquartered in Southlake, TX. He treats cold calling as one of the most persistent inefficiencies in how agent teams operate. His framework centers on what he calls commission-generating activities – or CGAs – the tasks that directly produce closed deals: showings, negotiations, client consultations, and active follow-up with warm prospects. Cold outreach, in his view, 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,” Nimergood says. Even rapid-fire dialing through 100 contacts takes one to two hours, time he says could go toward work that moves deals forward. For a team trying to scale, he argues, every hour an agent spends on cold outreach compounds into missed opportunities elsewhere.

How AI-Prioritized Call Centers Work in Practice

Top Gun Team has partnered with a company called Angel AI, which provides an AI-supported call center staffed by human callers based in Dallas–Fort Worth. The model works as follows: Nimergood’s team submits a call list and a script, and the call center handles the outreach. What distinguishes the service from a standard call center is a layer of what Angel AI calls “responsive AI” built into the process.

Before calls are made, the AI scours 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 are completed, the AI analyzes recorded conversations for buying signals, then generates a report identifying which contacts showed genuine interest.

Nimergood describes the output this way: of 100 people called, perhaps 10 answer, and of those 10, 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 what Nimergood considers the most operationally valuable part of the service. Rather than asking agents to make judgment calls about which cold contacts to prioritize, the system surfaces that information automatically, allowing agents to focus personal outreach on contacts who have already demonstrated engagement.

Filtering Out Dead Leads Before Agents Touch Them

The call center model also removes contacts from the pipeline entirely – not just warms them up. When AI analysis of a recorded call indicates that a prospect is no longer in the market, that contact gets archived rather than recycled back into the queue.

“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.”

Agent teams that manage large databases often struggle with stale leads – contacts who were once active but have since bought, rented, or moved on – continuing to consume outreach resources. A system that removes those contacts based on conversation analysis rather than manual review improves the signal-to-noise ratio in a team’s pipeline, according to Nimergood. Agents inherit a smaller, more accurate list rather than a bloated database full of dead numbers and disengaged contacts.

Domestic Staffing and the Limits of Full Automation

Nimergood is deliberate about one aspect of the Angel AI model he considers non-negotiable: the callers are human, and they are based in Texas.

He acknowledges that fully automated AI voice calling exists and will likely play a role in the industry eventually, but says the technology is not ready for deployment at scale. “I think that will have a place, and that does have a place in our industry, but not quite yet,” Nimergood says. “It hasn’t been ironed out or perfected yet.”

He also notes that outsourcing calls 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 – which carries reputational risk – and in-house agent calling, which carries an opportunity cost. For teams scaling quickly and managing large lead databases without pulling agents off higher-value work, this middle-ground approach addresses both concerns simultaneously.

Where This Fits in a Scaling Operation

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 the same principle to his team’s broader operations: agents focus on CGAs while support systems handle the lower-value tasks that feed the pipeline.

“If they want to be top-producing agents, they have to minimize their administrative time, and they have to maximize their CGA time,” Nimergood 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 actually translates into more closed deals, or just more unanswered calls piling up in an agent’s queue.

About the Expert: Justin Nimergood is the founder of Top Gun Team at Epique Realty and principal of Nimergood Real Estate, specializing in residential real estate across the Dallas-Fort Worth metroplex and California. Learn more at TopGunTeam.org.

Disclosure: Individuals or companies mentioned may have a commercial relationship with KeyCrew.