A trust + pricing data layer for the skilled trades — built inside one of the largest installer networks in the country.
A typical HVAC install: the homeowner writes a $10,000 check; the person who actually does the work takes home ~$1,000. The rest is materials, overhead, and a customer-acquisition machine. This is a market inefficiency, not just unfairness.
A $100M chain spends roughly 16% on marketing — more than it pays the technician. Top placement is bought, not earned. Pricing is opaque: a real-world example saw estimates for the same Lennox units quoted between $34,000 and $56,000.
That CAC + opacity layer is the value pool. It is large, structural, and entirely about acquiring the customer — not about doing the work better.
TradeOS removes the ~25% marketing-and-sales CAC layer. Ranking is earned by trust × fair price, not by who outspends. The freed value splits between the homeowner and the installer — the two sides of the trade that currently lose the most.
Licensed contractors imported, claimed, and verified — license, insurance, identity, history.
Real installs flow through the network — dispatch, scheduling, completion, QA.
Itemized pricing + trust events accumulate on every job — structured, not scraped.
Better matching attracts more demand, which pulls in more verified supply.
Each cycle deepens the data moat.
All figures reflect the current TradeOS dataset. Not a forecast.
License, insurance, identity, claim history, and operating behavior — bound to a resolved contractor entity, not a free-text business name.
Real itemized estimates and accepted prices by SKU, region, and job type. Not survey data. Not list price. The price that actually clears.
Entity resolution + the claim loop compound the moat: every claim, verification, and job tightens identity and adds structured trust events that no directory or rollup can replicate after the fact.
The re-rating thesis: a traditional contractor trades at a labor-business multiple. A platform sitting on a proprietary trust + pricing data network trades at a different multiple entirely.
Financial services — lending, insurance, and warranty — built on the trust + pricing data layer. Underwriting gets cheaper as the dataset deepens.
TradeOS converts a labor business into a data asset.
Multiples shown are illustrative ranges, not a forecast.
For diligence materials or a working session, reach the TradeOS team at investors@homealliance.com