Geospatial Engineering for Cost Seg™
Case study · Short-term rental
The Serrano Avenue
Cost seg lets you use part of your property's value to lower your income taxes. Here is how it worked for a 1927 single-family home, bought in 2021 and furnished for guests.
Where the $2.35M went
Component allocation
Year one, in dollars
| Accelerated depreciation | $195,257 |
| Total year-one deduction | $195,257 |
| Straight-line without a study | ~$19,404/yr |
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Explore the 3D PortalWhy this study reads the way it does
In Los Angeles, the land is most of the price
A short-term rental in central Los Angeles, where the dirt carries the value: our assessor record puts land at 80% of the price ($1,880,000), leaving a depreciable building of just $470,000. In a market like this the deduction is not won by a big building basis. It is won by classifying every component and every furnishing the building holds.
With land at 80%, the building is a sliver of the purchase. Cost segregation pulls the short-life components — finishes, fixtures, site work — out of the slow 39-year line, so $195,257 is deductible this year despite the modest $470,000 building basis.
No furnishing receipts, so the scan reads the listing photos across 14 rooms — an item seen in three frames counts once — and prices each piece at conservative catalog replacement value. That is $63,620 of furnishings the owner already bought, recovered on the five-year schedule.
This owner did not renovate, so there is no reconstruction write-off and none is claimed. The study is a clean itemized record of the building and its contents, which is exactly why a high-land property still produces a real first-year deduction.
The lesson. In high-land markets the building basis is small, so the deduction depends on classification density — how completely the components and furnishings are identified — not on the size of the basis.
The study
Six stages, from public record to engineered study.
Pick a stage to see what it did on this house.
Every part mapped and modeled
The Study Algorithm, running
The Study Algorithm
How we find the highest defensible deduction
Every house is different, so we run every supportable combination of methods and keep the biggest deduction the record can prove.
Defensibility, step by step
Only supportable methods count.
15-year site work and land improvements
Decks, paving, fencing, utilities and plantings recover over 15 years.
Your portal
Answer a few questions. We do the rest.
How the property is used, what you changed, what you furnished. We fetch the public record ourselves.
One fee, shown up front in the portal.
Turn the house, tap any part, follow the Spatial Graph and read the review.
Questions
Common questions about this study
- What does a real cost segregation study look like?
- This is a complete, engineering-reviewed cost segregation study on a short-term rental property. Every figure is computed by a deterministic engine from source documents, cited to the underlying tax authority, and reproducible, including a 14-room component reclassification and a full depreciation schedule. Addresses and client identities are changed for privacy; the facts and dollars are true engine output.
- How much does this study accelerate into the first year?
- The first-year deduction heads this page, and The Study Algorithm section builds it step by step from the run: the building's shell, each short-life class at 80% bonus depreciation, any remodel disposition and the Inventory.
- Is a cost segregation study like this defensible?
- It is built to the standards in the IRS Cost Segregation Audit Techniques Guide: each component is classified with a citation, the basis derivation is engineered rather than estimated, and every calculation is reproducible. Unlevered prepares and signs the engineering study; the property owner's CPA remains the sole tax return preparer.
- What makes these studies transparent?
- Every number traces to a source. The study shows the room-by-room allocation, the reasoning behind each component's classification, and a calculation that can be reproduced from the same inputs, not a black-box estimate.