05

What the Photos Don't Tell You.

AI sees what sellers hope you won't notice.

The Problem

Property transactions involve enormous sums and limited information. Buyers rely on listing descriptions written by sellers.

For property managers, assessing condition across dozens of properties requires systematic inspection — prohibitively expensive or simply not done.

What We Do

Upload property photos. Computer vision analyses visible condition: facade cracks, window deterioration, roof damage, moisture stains.

Combined with location data and comparables, the system generates a market value estimate and a renovation cost breakdown.

How It Works

01

Upload

Property photos + basic data (location, size, year).

02

Vision Analysis

AI identifies visible issues: structural, aesthetic, installation-related.

03

Condition Score

Each element rated: good / acceptable / needs attention / critical.

04

Valuation

Market value estimate based on location, condition, comparables.

05

Renovation Estimate

Itemized cost breakdown based on regional pricing data.

06

Document Processing

Energy certificates, contracts, registry records — extracted.

Technology

Computer Vision (GPT-4o)LLM AnalysisGeolocation DataPrice DatabasePydanticPostgreSQL

Concrete Example

An investor uploads 40 photos of a 6-unit building. System identifies: facade needs full renovation (€35,000), moisture damage (€8,000), original 1985 windows (€18,000). Total: €78,000. Investor negotiates price down by €60,000.

Ready to see what this means for your business?

Scope Your Solution →