Real estate concierge agent · WhatsApp + showings + pre-qualification
A boutique real estate firm with a premium portfolio in Mexico City. We built a WhatsApp agent that responds around the clock, captures leads from Meta Lead Ads and Lamudi, pre-qualifies borrowing capacity and books a showing with the right broker.
Boutique real estate firm (client under NDA)
The firm received a high volume of leads through Facebook Lead Ads and Lamudi, and the first response took hours. In real estate, replying within the first few minutes weighs heavily on the odds of landing a showing, and that bar was almost never met. Brokers complained about bad leads; marketing said the good ones were coming in — the problem was the filter and the response speed, not the source.
Stack and deliverable
A three-layer Studio agent: unified lead capture from Meta Lead Ads and real-estate portals into a single inbox; a WhatsApp conversation that qualifies intent (own home, investment, relocation), area and price range, with a short conversational pre-qualification covering income, age and credit history (a credit bureau check with explicit consent); and, if the lead qualifies, a guided showing booked on the calendar with the broker assigned to that area. If not, the lead moves into segmented nurturing with tailored content.
What changed in the operation
What we learned
Conversational pre-qualification (not a rigid form, but a natural dialogue that gathers data along the way) got more people to answer honestly about what they could afford. The initial friction was offset by the sense of personal attention. Another finding: qualified prospects saw the consented credit bureau check as a way to avoid wasting time on properties outside their range.
How it was built
Technology: WhatsApp Business Cloud API · Meta Lead Ads webhook · Lamudi/Inmuebles24 APIs · Calendly · Credit bureau opt-in · CRM
Delivery: Staged delivery through to production
FAQ · this case
How did this Residential real estate project make it to production?
Staged delivery through to production: design, build, testing with real data and launch. By the end, the client's team was running the agent in production, with observability dashboards and guardrails already configured. Stabilization is part of the delivery.
What tech stack was used in this Residential real estate case?
WhatsApp Business Cloud API · Meta Lead Ads webhook · Lamudi/Inmuebles24 APIs · Calendly · Credit bureau opt-in · CRM. Each piece was chosen to fit the client's existing systems — no forced migrations, integrating through official APIs wherever they were available.
How are results tracked?
Before the project starts, we agree on an operational baseline with the client, and during stabilization it's reviewed on the operations dashboard. Because of the NDA, we don't publish this client's figures. In the diagnostic we define what to measure in your case.
Can this be replicated at another company in Residential real estate?
The pattern is replicable; the specific implementation depends on the current stack, operating volume and internal rules. The Studio diagnostic identifies which pieces apply to your context and estimates the return for your case.
Who runs the agent after the project?
The client's team. Studio hands over the agent running and trains the team on monitoring, prompt adjustments and exception handling. Stabilization support is included for the first few months; after that, an optional monthly retainer is available.
What happens if the AI model changes or gets more expensive?
We don't depend on a single provider. If a model changes or gets more expensive, we move the agent to another one without rebuilding it.
Facing similar challenges in Residential real estate?
A Studio diagnostic with an architect. We identify which processes to automate first and estimate the return for your case.
No cost · No commitment