{"id":2954,"date":"2026-07-03T15:24:43","date_gmt":"2026-07-03T13:24:43","guid":{"rendered":"https:\/\/evana.ai\/?p=2954"},"modified":"2026-07-03T15:24:45","modified_gmt":"2026-07-03T13:24:45","slug":"aachener-grundvermoegen-datenextraktion-ki","status":"publish","type":"post","link":"https:\/\/evana.ai\/eng\/aachener-grundvermoegen-datenextraktion-ki\/","title":{"rendered":"Aachen real estate assets \u2013 from 15,000 documents to the basis for decision-making"},"content":{"rendered":"

How AI data extraction transforms 15,000 documents into a basis for decision-making.<\/strong><\/h2>\n\n\n\n

<\/p>\n\n\n\n

Aachener Grundverm\u00f6gen KVG manages a large international portfolio of documents: leases, energy performance certificates, appraisals, and numerous other records\u2014approximately 15,000 documents in total. However, much of this information was unstructured, difficult to access, and could only be analyzed with considerable manual effort. Therefore, Aachener Grundverm\u00f6gen KVG, in collaboration with EVANA, developed an AI-powered data extraction solution. This solution automatically recognizes document types, extracts defined data points, and presents all the information in a structured format. Both teams worked closely with the relevant departments to ensure the content was accurately represented.<\/p>\n\n\n\n

<\/p>\n\n\n\n

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problem<\/h3>\n\n\n\n

Important company data is contained in unstructured documents such as contracts, invoices, and receipts. Therefore, it is difficult to access, cannot be systematically analyzed, and can only be used with significant manual effort.<\/p>\n<\/div>\n\n\n\n

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Solution<\/h3>\n\n\n\n

EVANA developed an AI-powered data extraction solution. It automatically recognizes document types, extracts defined data points, and provides the results in a structured format, closely coordinated with the relevant departments.<\/p>\n<\/div>\n\n\n\n

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Result<\/h3>\n\n\n\n

A consistent, readily analyzable database was created from approximately 15,000 international documents. Manual data entry is eliminated, and decision-making quality improves.<\/p>\n<\/div>\n<\/div>\n\n\n\n

<\/p>\n\n\n\n

AI data extraction: from unstructured documents to a database<\/h2>\n\n\n\n

<\/p>\n\n\n\n

Managing an internationally diversified real estate portfolio generates a constant stream of documents of varying types, languages, and formats. Decision-relevant information is scattered within these documents and embedded in continuous text, rather than being presented in a format that allows for direct analysis. This is precisely where the jointly developed solution from EVANA and Aachener Grundverm\u00f6gen KVG comes in.<\/p>\n\n\n\n

EVANA's AI automatically analyzed approximately 15,000 documents. First, it identifies the document type, such as a lease agreement, energy performance certificate, or valuation report, and then extracts the previously defined data points. The relevant content was determined jointly by the relevant departments and EVANA, ensuring that the database precisely meets the company's requirements.<\/p>\n\n\n\n

The extracted information is then available in a structured format and can be processed directly. In this way, a robust foundation for reports, strategic decisions, and integration into existing systems is created from a heterogeneous collection of documents.<\/p>\n\n\n\n

<\/p>\n\n\n\n

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AI data extraction: Recognize document types, extract data points<\/h3>\n\n\n\n

After the upload, the EVANA AI automatically recognizes the document type and extracts the relevant data points, for example, terms from leases, amounts from invoices, or areas from valuation reports.<\/p>\n\n\n\n

Even with different formats and languages, the data collection process remains consistent. The collected information is then immediately available for further analysis and processing.<\/p>\n\n\n\n

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Get to know EVANA now<\/a><\/div>\n<\/div>\n<\/div>\n\n\n\n
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\"KI-Datenextraktion
EVANA recognizes the document type and automatically extracts the defined data points.<\/figcaption><\/figure>\n<\/div>\n<\/div>\n\n\n\n

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Defined together, exactly in the right format<\/strong><\/h2>\n\n\n\n

<\/p>\n\n\n\n

The value of a database arises where it aligns with actual processes. Therefore, EVANA did not predefine the relevant data points, but rather developed them collaboratively with the specialist departments of Aachener Grundverm\u00f6gen KVG. In this way, the solution captures precisely the information that day-to-day operations and analyses truly require.<\/p>\n\n\n\n

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\"\"<\/figure>\n<\/div>\n\n\n\n
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Structured output for reports, systems and decisions<\/h3>\n\n\n\n

The solution outputs the extracted data in the required target format, whether as CSV, Excel, or via an API. This makes it ready to use and allows it to be directly integrated into reports and existing systems.<\/p>\n\n\n\n

This transforms a scattered collection of documents into a consistent data foundation that bases strategic decisions on reliable information.<\/p>\n\n\n\n

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Book a demo now!<\/a><\/div>\n<\/div>\n<\/div>\n<\/div>\n\n\n\n

<\/p>\n\n\n\n

15,000 documents, a reliable data foundation<\/strong><\/h2>\n\n\n\n

<\/p>\n\n\n\n

Thanks to automated data extraction, Aachener Grundverm\u00f6gen KVG has access to a readily available and consistent database. No one has to manually extract information from individual documents anymore; instead, it can be analyzed directly. This significantly reduces workload and simultaneously improves the quality of decisions, as they are now based on a complete and uniform data set.<\/p>\n\n\n\n

<\/p>\n\n\n\n

\u201eWe are thrilled with the user-friendliness of EVANA360. EVANA combines a modern lifecycle data room with the most advanced artificial intelligence for the real estate industry.\u201c<\/em><\/p>\n\n\n\n

Nico Schr\u00f6der, Head of Innovation, Aachener Grundverm\u00f6gen KVG<\/p>\n\n\n\n

<\/p>\n\n\n\n

More than just data extraction<\/strong><\/h3>\n\n\n\n

<\/p>\n\n\n\n

The solution is based on the existing EVANA infrastructure and can be flexibly rolled out to other document types and use cases. This allows teams to quickly integrate new document types, define additional data points, and extend existing processes. The collaboration with Aachener Grundverm\u00f6gen KVG encompasses several projects: from the automated evaluation of physical land registers for property tax returns<\/a> about the AI-supported energy management<\/a> up to and including broad AI data extraction from the entire international document repository.<\/p>\n\n\n\n

This provides companies with a scalable solution to automatically analyze large volumes of documents and provide relevant information in a structured manner across various application areas.<\/p>\n\n\n\n

<\/p>\n\n\n\n

Frequently Asked Questions about AI Data Extraction<\/strong><\/h2>\n\n\n\n

<\/p>\n\n\n\n

How does AI data extraction from unstructured documents work?<\/strong>

During AI data extraction, the AI first automatically recognizes the document type, such as a lease agreement, invoice, or appraisal, and then reads the previously defined data points from the text. This transforms unstructured documents into structured, directly analyzable data, entirely without manual entry.<\/p> <\/div>

What document types can EVANA process?<\/strong>

EVANA processes documents such as rental agreements, invoices, energy performance certificates, appraisals, and other supporting documents. The AI also consistently recognizes different languages and formats within an international database. The teams add new document types as needed.<\/p> <\/div>

In what format will the extracted data be output?<\/strong>

EVANA provides the data in the required target format, for example as CSV, Excel, or via an API. This makes it ready to use and allows it to be directly integrated into reports and existing systems.<\/p> <\/div>

How did the project with Aachener Grundverm\u00f6gen KVG go?<\/strong>

EVANA automatically analyzed approximately 15,000 international documents for Aachener Grundverm\u00f6gen KVG. The relevant data points were defined jointly by both teams and the relevant departments, ensuring that the resulting database precisely meets internal requirements and serves as the basis for reports and decisions.<\/p> <\/div> <\/div>\n\n\n\n

<\/p>\n\n\n\n

About EVANA<\/strong><\/h3>\n\n\n\n

<\/p>\n\n\n\n

EVANA develops AI-powered solutions for analyzing large volumes of documents. Based on its own infrastructure, the AI automatically recognizes, extracts, and structures unstructured content. This gives companies faster access to relevant information and creates a reliable data foundation for analyses, processes, and decisions.<\/p>","protected":false},"excerpt":{"rendered":"

How AI Data Extraction Transforms 15,000 Documents into a Basis for Decision-Making: Aachener Grundverm\u00f6gen KVG manages a large, international collection of documents: leases, energy performance certificates, appraisals, and many other records\u2014a total of approximately 15,000 documents. However, much of this information was unstructured, difficult to access, and could only be analyzed with considerable manual effort. Therefore, Aachener Grundverm\u00f6gen KVG developed\u2026<\/p>\n

Aachen real estate assets \u2013 from 15,000 documents to the basis for decision-making<\/span> Read More \u00bb<\/a><\/p>","protected":false},"author":8,"featured_media":2960,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"disabled","footer-sml-layout":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center 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