Different companies. Different countries. One method.

Context

A 100-broker brokerage hired us after losing two deals, one worth USD 1.1 million and another worth USD 1.3 million. They thought they knew where their operational leaks were but couldn’t confirm it. They had already adopted several AI tools, and none was delivering results because none was being used properly.

The problem

• Client communication was scattered across text messages and different messaging apps.
• The CRM was generic, not built for real estate, and used halfway and without rules.
• Leadership found out a deal was at risk only after it was lost.
• New brokers took about six months to reach peak performance.

What we did

• We interviewed every level and traced real deals end to end, including the two lost ones, to find where follow-up broke.
• We brought everything into a single platform, ClickUp: the CRM, templates and client messaging, with one record per client and a mandatory next step on every deal.
• We audited the AI tools they already had, removed the ones that weren’t working and built the ones that were into the process.
• We built a dashboard with alerts for deals at risk.
• We documented the method of the top brokers and built the onboarding program from it.
• We trained the whole team and monitored adoption.

Quick wins

• All client messaging in one place, with templates for each stage.
• Every deal with an owner and a visible next step.
• Alerts when a deal goes days without activity.

Context

A brokerage working across two markets that ran on the people in it, not on the systems around them. That works while a company is small. When it tries to grow, the absence of systems becomes the ceiling.

The problem

• Every broker had their own way of following up with clients, managing listings and closing deals.
• A large share of the team’s time went to administrative tasks that required no real judgment.
• Critical information was not being captured anywhere.
• Pipeline visibility existed only in each broker’s head.

What we did

• We mapped how properties, clients and contracts were actually managed in both markets, including the informal workarounds built up over years.
• We built a framework that brought consistency to the client relationship without losing the personal touch that makes real estate work.
• We redesigned and shortened the contract processes and automated reporting.
• We made pipeline visibility shared and real time.
• We trained the whole team on the new tools and on using AI for reporting, communications and analysis, and stayed through implementation and the first months of adoption.

Quick wins

• Reporting automated.
• One shared, real-time view of the pipeline.
• A shorter, redesigned contract process.

Context

The Miami office of a brokerage with offices in several US cities, with a team of 50 brokers, was generating plenty of demand and losing a large share of it on the way.

The problem

• Portal inquiries arrived by email and on the front desk’s WhatsApp, and were forwarded by hand from chat to chat.
• Nobody owned the path from inquiry to broker, to showing, to offer.
• Each handoff dropped something: the client’s budget, the property they had asked about, what had already been promised.
• More than a third of inquiries got no first contact on the day they arrived, and clients had to tell their story again at every step.

What we did

• We followed real inquiries from the first message to the signed contract, and talked with the front desk, the brokers, the transaction coordinator and the owners.
• We found the six points where the work changed hands without an owner or a deadline.
• We gave every handoff one owner and one maximum time, and built a single record per client with a mandatory next step.
• We set up an automatic assignment that notifies the broker on duty by message.
• We put AI into the handoffs: Claude summarizes each conversation and the client’s needs before every handoff, and drafts the first reply for the broker to review and send.
• We trained the whole team on the new flow and on working with AI, and stayed through the first months to adjust it with the numbers in hand.

Quick wins

• Every inquiry assigned automatically to the broker on duty.
• One record per client, with a mandatory next step.
• A named owner and a maximum time for every handoff.

Context

A sales-focused agency in Paraguay with eight brokers found out about its problems too late.

The problem

• Each broker kept their own spreadsheet.
• The owners saw the real state of the pipeline only when the month closed, after two days of copying figures by hand.
• A negotiation that had gone cold was usually discovered when the client had already signed with another agency.
• Decisions on prices, advertising and which brokers needed support were made on information that was weeks old.

What we did

• We sat with each broker and with the owners to see how a deal was really followed from first inquiry to deed, and which unwritten signals told them a deal was in trouble.
• We turned those signals into four indicators: inquiries, visits, reservations and days without movement per deal.
• We built a shared board where every deal lives in one place, with one rule: any deal with no activity for ten days turns red and alerts the broker and the owners.
• We put AI into the weekly review: every Monday Claude reads the board and writes the summary of what moved, what stalled and a suggested next step for each deal. Brokers and owners decide what to do.
• We trained the brokers and the owners on the board and on using AI to prepare their follow-ups, and stayed through the first quarter to adjust the rules.

Quick wins

• Every deal in one shared board.
• A red flag and an alert after ten days without activity.
• A monthly report no longer copied by hand.