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Case studies

The systems we build.

Representative examples of the systems we build for real estate companies — a typical problem, what a solution looks like, and what changes once it is live. These are illustrative scenarios drawn from the kind of work we do, not accounts of named clients.

Real estatethe only industry we build for
CRM · data · toolswhat most engagements combine
Yardi · QuickBooks · MLSintegrations we’ve shipped against
Illustrativerepresentative of the systems we build
CRM & pipeline
½ day → liveweekly pipeline report
~60agents on one system
Challenge

Roughly sixty agents were spread across four disconnected places: a prior CRM that had quietly turned into a stale contact list, the MLS for live listing data, a shared drive of per-agent deal spreadsheets, and individual email inboxes where most of the real movement on a deal actually lived. Listing status sat in one place, the buyer's loan and option-period dates in another, and commission splits in a third, so the same deal had to be re-keyed two or three times — and was routinely wrong somewhere. Every Monday a transaction coordinator rebuilt the leadership pipeline report by hand: pulling each agent's tab, reconciling it against the MLS, chasing people for missing close dates, and pasting it into one master sheet. It took most of a morning, and by the time it reached the 11 a.m. sales meeting it was already out of date.

What we built

A custom CRM and deal pipeline modeled directly on the brokerage's own listing and buyer stages — not a generic funnel — with separate tracks for listing-side and buyer-side deals (New Lead → Appointment → Active / Under Contract → Option & Inspection → Clear to Close → Closed). We wired in a one-way MLS feed so listing status, price changes, and key dates sync automatically instead of being copied across, and an email integration that logs correspondence against the right contact and deal so history stops living in private inboxes. A read-only sync to their accounting tool ties each closed deal to its commission split. Role-based access gives agents their own book of business, coordinators a cross-agent task and document view, and managers a brokerage-wide pipeline with drill-down.

Result

One source of truth for the whole brokerage. The Monday pipeline report — previously most of a coordinator's morning, every week — is now a live dashboard leadership opens themselves, so the sales meeting starts from current numbers instead of last week's. Because listing data flows from the MLS and email logs itself against the deal, agents stopped re-keying the same deal across three tools, which removed the most common source of mismatched dates and dollar figures. Coordinators got that recurring half-day back, and for the first time managers can see at a glance what is under contract, what is sitting too long in a stage, and which deals are at risk — live, not at the end of the week.

Data & dashboards
~2 days → ½ dayfirst-pass deal review
1 modelper deal, sourcing to decision
Challenge

Every opportunity was evaluated in a fresh copy of a master Excel model, so each analyst's deal quietly drifted — different rent assumptions, different return assumptions, formulas overwritten under deadline. Pipeline status lived in a color-coded tracker and in people's heads, with no portfolio-level view of what was live, passed, or under offer. The real pain was the fortnightly review pack: an analyst spent the best part of a day before each meeting re-keying numbers out of a dozen deal files into one comparison deck, and figures still had to be reconciled by hand because no two models were built the same way. When the partners asked "how many deals did we look at in this submarket last quarter, and why did we pass," nobody could answer without reopening old spreadsheets.

What we built

A deal-sourcing and analysis dashboard sitting on a data pipeline that ingests listing and market data — agent and authorized listing feeds, the firm's off-market leads via a monitored inbox, and reference data for comparable market inputs — then normalizes it into one canonical deal model. Every opportunity is evaluated against the same template, with assumptions versioned and locked, so a deal is assessed the same way whoever sources it, and it moves through defined stages from first look to close. The dashboard rolls the whole book up by submarket, strategy and status. Roles separate analysts, the acquisitions lead, and read-only partners; the review pack is generated live from the same models rather than rebuilt by hand, with an audit trail of who changed which assumption and when.

Result

A first-pass deal review that used to take roughly two days of an analyst's time now lands in about half a day, because the model, comps and market inputs are already in place instead of being assembled from scratch. The pre-review scramble is gone: the review pack is generated from live deal models, so the half-day of manual re-keying and reconciliation before each meeting dropped to effectively none — and the numbers in the screening model and the final model are now the same number by construction. The partners finally have one live view of the pipeline — every deal sourced, advanced or passed, with its status and the reason — so quarterly questions about deal flow by submarket are answered in the tool instead of by archaeology through old files.

Internal tools
3 days → liveowner month-end report
~2,400units on one system
Challenge

Across roughly 2,400 units across one metro area, the team ran the business out of an inbox and a folder of spreadsheets. Leasing was a shared workbook that two coordinators edited at once and routinely overwrote; maintenance lived in a property@ inbox where a tenant's request, a contractor's reply, and the building manager's note sat in three separate threads, so tickets were acknowledged late and sometimes not at all. The part that actually hurt was owner reporting: every month-end, two staff spent about three days exporting figures from Yardi and QuickBooks, reconciling them against the rent roll in Excel, and hand-building a per-owner PDF report — and because each package was assembled by hand and emailed individually, errors slipped through and owners with multiple buildings would call asking why one property's numbers did not tie out.

What we built

A set of internal tools wrapped around how the team already worked, not a rip-and-replace. A leasing pipeline moved every prospect through Inquiry → Showing → Application → Screening → Approved → Lease signed, with one record per unit so coordinators stopped overwriting each other. A maintenance tracker turned inbound requests into tickets with a category, priority, an assigned building manager or contractor, and a status — New, Assigned, In progress, Awaiting parts, Done — plus automatic acknowledgement to the tenant and reminders on anything aging past its SLA. An owner reporting portal gave each owner a secure, live view of their building(s): rent collected, arrears, occupancy, open and completed work orders, and the monthly report, with multi-building owners rolled up correctly. Under the hood we integrated their existing stack — read-only syncs from Yardi (rent roll, ledgers, units) and QuickBooks (owner-level income and expense), inbound email parsing for maintenance, and document storage — so figures came straight from the systems of record instead of being re-keyed.

Result

The month-end owner report went from a roughly three-day, two-person assembly job to a portal that is simply live and reconciled all month, so owners stopped emailing to chase statements and the accounting lead got the first week of the month back. Maintenance requests now get acknowledged automatically the moment they land instead of waiting in an inbox, and because every ticket has an owner, a status, and an SLA timer, the operations director can see what is stuck before a tenant or owner escalates. And because leasing, maintenance, and owner figures all read from the same connected data, staff stopped re-keying between Yardi, QuickBooks, and spreadsheets — and the numbers an owner sees finally match the numbers the team sees.

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