Automation in the real estate market with AI: a project insight
The real estate market is undergoing a technological upheaval. Whereas in the past, analog processes, paper-based documentation and tedious manual research characterized everyday life. Now, automation and artificial intelligence (AI) are moving more into the focus of the industry. There is a paradigm shift in data processing in particular: instead of endless spreadsheets and manually maintained CRM systems, AI-supported systems enable precise, efficient and error-free information management.
As neuland.ai, we support companies from the real estate sector as well as many other industries on this path and develop innovative AI solutions that change the market in the long term.
One example of this is our project with SAEGER & CIE. Investments GmbH. This article provides an in-depth insight.
Challenges in the real estate sector
A look at the challenges in the real estate sector shows that many processes are still inefficient and can be optimized using modern technologies and digitalization:
The real estate industry faces the challenge of managing data volumes efficiently while at the same time meeting the increasing demands for transparency and efficiency. Maintaining and updating portfolio and customer data in particular are complex tasks that are often time-consuming and error-prone using conventional methods.
A key problem is bringing together information from different sources – including rental processes and contracts, energy bills, market analyses and customer contacts. Much of this data exists in separate systems or even in analog documents, creating redundancies and inconsistencies. This makes precise data analysis difficult and leads to delays in investment decisions and sales processes.
In addition, regulatory requirements in the real estate sector are increasing, which require error-free and traceable data management. Precise and up-to-date data processing is essential, particularly in real estate valuation and price forecasts, in order to enable well-founded economic decisions. Missing or outdated information can cause miscalculations and delay potential business opportunities.
A concrete example of this challenge is the maintenance of CRM data. As an established company with high demands on data quality and business processes, SAEGER & CIE. SAEGER & CIE. faced the challenge of efficiently managing thousands of CRM entries. A recurring problem here was the addition of missing contact data, in particular telephone numbers of potential customers and business partners. The previous manual research required considerable resources and was very time-consuming. External service providers also did not always provide up-to-date and accurate data, which could affect the reliability of contacting.
The solution
AI-supported telephone number search
The challenge was to automate telephone number research in order to optimize contact management and acquisition processes. To solve this problem, we at neuland.ai implemented a highly developed AI-supported telephone number search.
How does this work in detail?
24/7 automatic phone search in the background
The core of our solution lies in the fully automated search for missing telephone numbers around the clock. A task in the background first checks all existing CRM entries. If a phone number is missing, the AI starts a multi-stage search routine. As soon as all previous contacts have been analyzed, the system takes over the ongoing monitoring of new entries. As soon as a new contact is added to the CRM or an existing entry is updated, the AI automatically starts the search for the missing number.
The AI systematically analyzes various data sources, including business directories, publicly available company websites and other relevant databases. By combining web crawling and semantic analysis, the AI can precisely identify telephone numbers and transfer them to the CRM system. A confidence matrix is used to evaluate the hit probability of each number found. Only reliable data is saved, avoiding unnecessary queries or incorrect entries.
The AI searches phone numbers in relevant databases, business directories and official company websites to provide accurate contact details. Real estate market with KI
Manual phone search for special cases
Users can search individual contacts via a web interface if special validationis required. Address fields (street, house number, zip code, city) can be customized separately to narrow down the search.
Optimized hit rate through machine learning
Our AI uses machine learning to specifically evaluate the telephone numbers found and ensure their relevance and accuracy . Generative AI, in particular LLMs, is used to deliver the best possible results. This intelligent evaluation process gives the system a high degree of precision in identifying the correct numbers.
The system stops the search as soon as a perfect match is found. If there is no clear result, up to five alternatives are presented to allow the user to make an informed choice. This gives users a reliable selection and allows them to choose the best possible option if required. This approach not only maximizes the hit rate, but also reduces the risk of incorrect entries.
Visual representation of a spiral process for telephone number validation with four steps: telephone number comparison, relevance assessment, secure adoption and generation of alternative suggestions.
Efficient control and automation
To ensure maximum transparency and traceability, all search processes are fully documented. Each telephone number researched is given a unique label to indicate that it has been found and validated by the AI. The AI assistant automatically saves new telephone numbers in the CRM system with a special comment so that it is possible to check exactly which number was found by AI
This automatic documentation not only ensures clarity within the company, but also facilitates future data checks. In addition, the CRM system is relieved of redundant tasks through automation, allowing employees to concentrate on value-adding activities.
Results and added value for SAEGER & CIE.
The implementation of this advanced AI technology has brought a number of concrete benefits for SAEGER & CIE:
Diagram showing the results of AI implementation in the real estate market, including cost optimization, reduced manual work, faster new customer acquisition and improved data quality.
Further automation potential in the real estate market with AI
In addition to the optimization of data management and customer interaction, there are numerous other automation potentials that have the potential to change the industry in the long term.
A digitalization study conducted by the German Property Federation (ZIA) in collaboration with EY Real Estate shows that over 90% of the companies surveyed see automation through digital technologies as a means of securing their long-term existence . Particularly high automation potential was identified in the areas of invoice processing (78%), payment transaction management (69%) and data transfer between systems (67%).
One particularly promising area is real estate valuation and price forecasting. AI-supported models not only analyze traditional factors such as the location, size and condition of the property, but also incorporate extensive socio-demographic data, economic developments, infrastructure projects and environmental factors. By analyzing these diverse data sets, more precise predictions can be made about future price trends, providing investors and real estate companies with a more sound basis for decision-making.
Further automation potential lies in contract management and due diligence. Reviewing contracts and legal documents is often time-consuming and error-prone. AI systems can significantly speed up this process by automatically analyzing large volumes of documents, extracting relevant information and identifying potential risks in contractual clauses. This enables a faster and more accurate valuation of real estate transactions. In addition, AI-supported systems can create standardized contract templates that are based on best practices and legal requirements.
Customer service in the real estate sector is also increasingly benefiting from AI. Chatbots and virtual assistants enable round-the-clock support for prospective buyers and tenants. By analysing customer preferences and behaviour, personalized property suggestions can be made, which significantly increases the efficiency of marketing processes. Routine inquiries such as appointments or property information can be processed automatically so that employees can concentrate on more complex advisory services.
One particularly innovative field is the integration of AI into virtual viewing technologies. Advanced AI models can generate detailed 3D models from two-dimensional images, enabling realistic virtual tours of properties. In addition, personalized virtual staging options can be offered by adapting furnishings and decoration to the viewer’s taste in real time. AI can also visualize different renovation scenarios and calculate their impact on the property value, helping both buyers and sellers in the decision-making process.
These automation options show that artificial intelligence is far more than just a tool for data analysis. It can revolutionize processes, increase efficiency and make the real estate market more transparent and customer-friendly. Companies that embrace these technologies at an early stage will secure competitive advantages in the long term and strengthen their market position.
Conclusion
Through our work at neuland.ai , we have shown how the targeted use of AI helps to solve specific challenges in the company and fully exploit efficiency potential.
This solution is not limited to SAEGER & CIE. – it offers immense added value for real estate companies, brokerage firms and investment companies that want to optimize their data processes.
AI-based systems like this are setting new standards in automated data enrichment and customer acquisition in the real estate sector. Those who actively shape this development will secure a decisive advantage in the long term.
