Traditional SFR
At 7–8% rates, single-tenant rents don't cover mortgage plus expenses on $150–250K homes in our target markets. One lease equals one point of failure.
A 6-bedroom home in our target markets loses $1,600/month leased as a whole house. Rented room-by-room at $550 per key, the same asset cash-flows $500+/month after debt service. This structural inefficiency exists across dozens of secondary U.S. markets because no one has built a professional, scalable platform to exploit it — until now.
Home prices and rents have outpaced wages for a decade. Remote workers, tradespeople, and recent graduates cannot justify $1,500+/month for a one-bedroom. At $550–650 per room with private locks and responsive management, we are the premium shared housing option — not the last-resort one.
Two identical homes. Two operating models. The difference between capital destruction and compounding returns.
At 7–8% rates, single-tenant rents don't cover mortgage plus expenses on $150–250K homes in our target markets. One lease equals one point of failure.
14–30% cash-on-cash returns. Break-even at 65.5% occupancy. $550 per room — half the rent of a one-bedroom apartment in the same city.
Three years. Four properties. Twenty-two rooms. Every system built from experience — not from a spreadsheet.
Every venture-backed competitor in shared housing shut down. We studied each one, identified the fatal flaw, and built around it: we own the asset, we target mid-market suburban, and we acquire — we do not develop or master-lease.
| Company | Model | Failure Mode | Outcome |
|---|---|---|---|
| Common | Master lease, urban | High overhead, lease liability | Shut down |
| Quarters | Master lease, urban | Lease exposure, thin margins | Shut down |
| Starcity | Development, luxury | Capital intensity, slow scale | Shut down |
| The Collective | Development, luxury | Massive cost overruns | Shut down |
| HubHaus | Master lease, SFH | 30% COVID vacancy | Shut down |
| PadSplit | Marketplace (no RE risk) | — | Surviving |
| This Platform | Own assets · mid-market suburban | Acquisition-only · no master lease | Operating · cash-flowing |
Four-phase screening: financial modeling → social demand → legal and risk review → boots-on-the-ground validation. Denver isn't even in our top markets — it's just where we proved the model.
Purchase prices $500K+ below Denver with comparable room-rent demand.
Fund I is a proof-of-concept raise, sized to acquire 75+ properties, prove the city-manager model works beyond our operating geography, and set up Fund II at 3× the scale.
Capital flows into real estate — not overhead. Over 75% goes directly into down payments on cash-flowing assets.
9% preferred return, cumulative. Full capital returned before the GP earns a cent of profit share. Tiered carry above the hurdle aligns our incentives with performance — the better the fund does, the more aggressively we share in it, and the more aggressively you do too.
| Return Tier | LP Split | GP Split |
|---|---|---|
| 0–9% (Below Hurdle) | 100% | 0% |
| 9–12% (Base Carry) | 80% | 20% |
| 12–18% (Strong) | 65% | 35% |
| 18%+ (Exceptional) | 50% | 50% |
A $12.5–25M+ exit target at platform maturity. Fund I is the wedge — a deliberately constrained raise sized to prove replicability across three markets without over-committing LP capital before the city-manager model is validated at scale.
Three principals. Operating experience running the exact model Fund I will scale. A governance structure designed around risk isolation, not founder convenience.
Strategy, acquisitions, underwriting. Mechanical engineer (Colorado School of Mines) with a Colorado real estate license and a background in oil and gas operations and sales. Three years operating room-by-room properties.
Operations, systems, city managers. M.S. Mechanical Engineering (Colorado School of Mines), Colorado real estate license, aerospace manufacturing and operations background. Built every operational SOP and the tenant qualification model.
Investor relations, capital partners, fund positioning. PhD Computer Science, Executive MBA (MIT). 40 years of federal executive leadership, including service as Chief Data Scientist at USCYBERCOM and Associate Director at the FDA.
We're speaking with a limited number of accredited investors before the Fund I allocation closes. Request the full deck and the property-level financial model.