{"id":2931,"date":"2026-06-19T13:49:34","date_gmt":"2026-06-19T11:49:34","guid":{"rendered":"https:\/\/evana.ai\/?p=2931"},"modified":"2026-06-19T13:49:36","modified_gmt":"2026-06-19T11:49:36","slug":"datengetriebene-immobilienentscheidungen-der-zukunft","status":"publish","type":"post","link":"https:\/\/evana.ai\/eng\/datengetriebene-immobilienentscheidungen-der-zukunft\/","title":{"rendered":"Data-driven real estate decisions of the future"},"content":{"rendered":"

Finding funding for real estate: how AI takes over document verification<\/strong><\/h2>\n\n\n\n

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Which funding program is right for my property, and do I even meet the requirements? For many real estate companies, this is where a lengthy process begins. The answers are buried in appraisals, energy performance certificates, and contracts\u2014often scattered across hundreds of documents. Searching for them can take days. With our first use-case webinar, we'll show you a faster way to check for funding eligibility using AI: EVANA makes your documents accessible, and our AI assistant EVA answers your questions in minutes. <\/p>\n\n\n\n

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Initial situation<\/h3>\n\n\n\n

A company wants to apply for subsidies for its properties. But which subsidies are available, and for which is it eligible? The necessary information is scattered across hundreds of documents.<\/p>\n<\/div>\n\n\n\n

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measure<\/h3>\n\n\n\n

All object documents are uploaded to EVANA. There, they are classified, duplicates removed, and structured. The AI assistant EVA searches the entire data space using a questionnaire for eligibility review.<\/p>\n<\/div>\n\n\n\n

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

Verifiable answers in minutes instead of days. Based on this, R3LEAF<\/a> complete the funding check and apply for the appropriate funding with pinpoint accuracy.<\/p>\n<\/div>\n<\/div>\n\n\n\n

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The webinar on the funding use case<\/strong><\/h2>\n\n\n\n

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Martin Teiber and Sebastian Deppe from EVANA, together with Tore Waldhausen from R3LEAF, will demonstrate what AI-powered grant application review looks like in practice and how quickly EVA can do it.<\/p>\n\n\n\n

With EVANA, documents are uploaded, automatically classified, and organized into a clear folder structure. The unstructured collection is transformed into a searchable data space. Based on this, EVANA, the AI assistant, answers the uploaded checklist, and these results are then used by R3LEAF for the funding review. The result: applying for funding in minutes instead of days.<\/p>\n\n\n\n

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Smart funding checks with AI from EVANA<\/strong><\/h2>\n\n\n\n

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Structuring and making object documents usable<\/strong><\/h3>\n\n\n\n

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It all starts with a mountain of documents: appraisals, energy performance certificates, contracts, land registry extracts, technical documentation. Everything pertaining to a property is uploaded to the EVANA AI document management system. There, our AI automatically sorts the files. It recognizes the type of document, assigns consistent names, and stores everything in a clear folder structure. Unsorted documents are transformed into an organized, classified data space, the foundation for AI-powered grant application review. <\/p>\n\n\n\n

EVA answers the questionnaire for the funding review<\/strong><\/h3>\n\n\n\n

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Now our AI assistant EVA takes over. The company provides her with a checklist\u2014a questionnaire containing everything relevant for the grant application. EVA then searches the entire data room, answers each question, and exports the answers as a file. What would take an employee days to compile manually, EVA accomplishes in just a few minutes.<\/p>\n\n\n\n

Speed isn't the only crucial factor. Grant applications have clear eligibility requirements, and accuracy in every detail is paramount. That's why EVA doesn't estimate; it reads directly from the original documents. Every answer can be traced back to its source and is verifiable. This ensures certainty: ultimately, the right funding is applied for based on a reliable foundation.<\/p>\n\n\n\n

Structured data for grant application review using AI<\/strong><\/h3>\n\n\n\n

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The process doesn't end with EVA's responses. The structured results can be directly transferred to other systems and processed further. R3LEAF demonstrates exactly this in the webinar. Instead of reviewing thousands of documents themselves, the team takes the processed data from EVANA and immediately starts the funding check. The tedious preliminary work is already done, and the path to the right funding is significantly shorter.<\/p>\n\n\n\n

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With EVA, we receive building data of a quality that allows us to work with it immediately. Leafund imports the information directly. Our funding bot then uses this data to find the right subsidies. This clean data foundation is exactly what we were missing before.<\/p>\nTore Waldhausen, CEO R3LEAF<\/cite><\/blockquote>\n\n\n\n

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The advantages of the funding check with AI<\/strong><\/h2>\n\n\n\n

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Time savings: from days to minutes<\/strong><\/h3>\n\n\n\n

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The biggest advantage of AI-powered grant application reviews is time. Manually reviewing large volumes of documents ties up employees for days. EVA delivers the same answers in minutes. The time saved is then channeled where it counts: into the decision and the application itself.<\/p>\n\n\n\n

Single Source of Truth for Real Estate Data<\/strong><\/h3>\n\n\n\n

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All object documents converge in EVANA. This creates a single, reliable data source instead of scattered versions on network drives and in different systems. Everyone works with the same version, and downstream tools also access the same foundation. We show how this foundation is created in the article on... AI integration into existing systems <\/a>Document management systems<\/a>.<\/p>\n\n\n\n

Further use cases for EVANA in the real estate industry<\/strong><\/h3>\n\n\n\n

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The funding check is just one example. It's based on a principle that can be applied more broadly: a structured data space, a suitable questionnaire, and EVA (Individualized Process Output) that brings both together. The same mechanism helps with many other tasks.<\/p>\n\n\n\n