"AI cost segregation" is a marketing label that means different things at different vendors. Here's what we mean by it, and what to look for in a credible automated study.
What the automation actually does
Our cost-seg engine ingests property characteristics (address, basis, purchase date, property type, key building data), pulls cross-verified third-party data (county assessor, RentCast, OSM building footprint, satellite imagery), and applies the same industry-standard 2026 construction cost data component cost library + MACRS classification rules a human engineer would apply. It runs hundreds of decisions in seconds.
The engine is not a free-form LLM. It's a deterministic pipeline with documented data sources, a 16-check QC gate, and internal technical review on flagged outputs. The output is the same kind of CPA-ready PDF a traditional firm produces.
Why it costs less
Most of a traditional firm's cost is project-managed labor — discovery calls, on-site visits, bespoke reporting. The IRS doesn't require any of that for a defensible study. industry-standard construction cost data, satellite imagery, and county assessor records cover what an on-site engineer would observe for a typical residential or small-commercial property.
Where it's not the right fit
Very large commercial (100+ unit MF, hospitality REITs), specialty industrial with custom MEP, and properties with unusual construction features that aren't well-represented in the cost library. For those, we'll tell you up front that a traditional firm with on-site engineering is the better call.