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Automated data extractionfrom property appraisals.

Upload appraisal reports. AI extracts cadastral data, occupancy, discrepancies and financial values for structured property profiles.

From PDF to fields
PDF appraisals · AI extraction · Structured data

Inside every appraisal.The information you need.

Cadastral details, occupancy, discrepancies, remediation and financial values are scattered across pages of documentation. This project uses AI to extract them into the fields needed for a property feasibility profile.

  • Document AI
  • Information extraction
  • Excel / CSV

From PDF to property profile.

Three illustrative views of the extraction workflow, based on the project field map. The property records and financial values shown are examples.

01 · From PDF to fields

Upload a report. Give its data structure.

An uploaded appraisal and the fields extracted by AI, side by side. Cadastral details, occupancy, building age, discrepancies and appraised value become accessible information.

02 · Extracted details

Every detail. In the right field.

The structure follows the project field map: ownership and cadastral data, issues, required works and costs. The view distinguishes available values from information absent from the document.

03 · The property profile

Organised data. Ready for your workflow.

Extracted information sits alongside auction data already collected from the portal. Budget, tax and other operator inputs remain separate. Excel or CSV output supports the next step: completing the property feasibility profile.

What we designed.

We developed the extraction engine that turns appraisal content into structured data. The schema defines which information to find and how to organise it, keeping document data, portal data and operator inputs distinct.

01

Upload appraisals

The workflow starts with text-readable PDF appraisals and available financial data in Excel or CSV. Documents and sources are prepared for processing.

02

Extract information with AI

The model identifies information defined in the schema: ownership, cadastral data, description, occupancy, discrepancies, issues, value and remediation costs.

03

Return structured fields

Excel or CSV output makes data available to the operator for the subsequent completion of the feasibility profile and use in business workflows.

Input data

PDF appraisals and available data

Processing

AI extraction against a defined schema

What it enables

Structured Excel / CSV fields

What it makespossible.

  • Property data organised in the agreed schema.
  • Document information available without transcribing every field.
  • Structured output ready for the feasibility profile.

From your documents.To the data you need.

From your documents. To the data you need.

Tell us about your project
Conceptual architecture: data, scientific knowledge, an AI assistant and an optimization roadmap.
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Your people, your processes or a new project. Let’s find the right place to start.

Or email us directlyinfo@icarex.ai

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