{"id":27553,"date":"2026-04-08T09:16:20","date_gmt":"2026-04-08T07:16:20","guid":{"rendered":"https:\/\/daisec.de\/?page_id=27553"},"modified":"2026-04-08T11:07:37","modified_gmt":"2026-04-08T09:07:37","slug":"traumhaus-assistent-ki-chatbot-fertighaeuser","status":"publish","type":"page","link":"https:\/\/daisec.de\/en\/praxisbeispiele\/traumhaus-assistent-ki-chatbot-fertighaeuser\/","title":{"rendered":"Dream Home Assistant \u2013 an AI-powered chatbot to help you choose the right prefabricated home"},"content":{"rendered":"
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How do you find a prefabricated house that truly meets your needs? The Dream Home Assistant shows how artificial intelligence (AI) can support the process from identifying your requirements to selecting the right house.<\/p>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n

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High demand, complex advisory situations<\/h5>\n <\/div>\n <\/div>\n
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Two companies in the prefabricated housing sector are facing a challenge: demand for housing is growing, whilst at the same time the consultation process is time-consuming. Many customers find it difficult to articulate their requirements, which makes it harder to assess their needs. However, there is also significant potential: standardised digital processes can reduce costs and make it easier for customers to find suitable options.<\/p>\n <\/div>\n <\/div>\n

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The aim: AI-powered support tailored to individual needs<\/h5>\n <\/div>\n <\/div>\n
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As part of the \u201cDream Home Assistant\u201d project, DAISEC is working with two companies to develop an AI-powered prototype that systematically identifies customers\u2019 basic needs and suggests suitable prefabricated homes. In the long term, this approach aims to ease the burden of the initial contact whilst offering customers an accessible overview of suitable house models. Furthermore, the prototype highlights the technical and organisational challenges that can arise during the development of a chatbot.<\/p>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n

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From customer request to recommendation: the prototype<\/h5>\n <\/div>\n <\/div>\n
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The prototype follows a clearly structured process in which several system components interact (see Figure 1). Customers begin the dialogue by freely describing their dream home. The chatbot then asks specific questions about the most important selection criteria, such as floor space, roof shape and the number of bedrooms (see Figure 2). These and other categories form the basis for the subsequent recommendation and enable a systematic assessment of the customer\u2019s needs.<\/p>\n

User inputs are collected and categorised within the dialogue and processing logic. The backend component controls the entire dialogue flow and generates a prompt from it, which is then sent to the AI model. The language model runs on a server and is accessed via an API key.<\/p>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n

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The AI model processes the structured customer requirements alongside a defined role description and the complete catalogue, which contains all available prefabricated house models meeting the same criteria. Based on this data, the model identifies the most suitable house and provides a reasoned recommendation.<\/p>\n <\/div>\n <\/div>\n

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Lessons Learned: Insights from the project<\/h5>\n <\/div>\n <\/div>\n
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The development of a reliable AI chatbot often hinges on many small but crucial details. In particular, data quality, dialogue logic and the control of the AI model have a significant impact on the system\u2019s reliability.<\/p>\n

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