AI powered real estate investment analyzer for Crowdia

A search filtered by yield never returns anything, and not from a bug but from arithmetic. Crowdia flipped the question: it takes the deal the investor already has and says what it would have to be bought at.

AI powered real estate investment analyzer for Crowdia

AI powered real estate investment analyzer for Crowdia

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The challenge

Crowdia evaluates real estate investment opportunities in Spain. Its user wants to know whether a home is a good investment, and the product started as a search filtered by yield.

That framing does not work, and the reason is arithmetic: requiring a given yield on total investment means buying at around half the market value of the refurbished property, and nothing is listed at that price on the open market.

  • The open market has no such deals: what clears the threshold is negotiated, not published.
  • Heterogeneous sources: every portal describes a property its own way, in text and images that need interpreting.
  • A number that decides a purchase: if the figure comes from a language model, it changes when the model changes.

Getting this wrong does not produce a bad recommendation: it produces an investment decision made on a calculation nobody can reproduce.

The solution

We flipped the product question: instead of searching for the deal that clears the bar, the system takes the one the investor already has and says what it would have to be bought at.

And the architectural principle that makes it trustworthy is the split between what interprets and what calculates.

The analyzer, on any property

  • The user provides the listing link, its description or screenshots.
  • The system returns yield, capital required, the maximum price at which the numbers work and the checks to run before signing.
  • It does not depend on the property being in a connected source.

AI interprets, the engine calculates

  • The AI layer reads the listing, interprets text and images, classifies, detects signals and returns structured variables.
  • The calculation engine takes those variables with the business configuration tables and resolves every figure deterministically.
  • The economic result is auditable and reproducible, and does not depend on the language model used.

The finder, on the same engine

  • It walks the sources of a defined target area and analyzes what it finds in batches.
  • Per portal connectors that the analyzer reuses to read a specific listing in depth.

Architecture and technology

  • Interpretation layer with language models and a deterministic calculation engine, separated by design.
  • Per portal connectors shared between the finder and the analyzer.

Learn more about software development and artificial intelligence.

The result

The product stopped promising an impossible search and started answering the question the investor can act on: how much to negotiate.

Starting point

  • Initial framing as a yield filtered search, which by arithmetic returns nothing.
  • Heterogeneous sources, each portal with its own listing structure.

Strategic impact

  • The analyzer works on any open market property, connected or not.
  • The report gives a maximum price and how much to negotiate, which is the actionable part.
  • Figures are auditable and reproducible because the language model does not produce them.
  • Changing models cannot alter the yield of a deal.

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