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Location analysis

Use Case

Location analysis

A machine learning algorithm analyses the properties and historical and current data of a property. This results in a score by which the attractiveness of an object can be evaluated.



In the real estate sector, assessing the attractiveness of the situation remains a key success factor.



Machine Learning algorithms can help to assess attractiveness by evaluating historical sales and offer data and automatically analyze the proximity to highways, public transport, popular restaurants, residential areas and shopping opportunities using satellite images.



Taking into account the pre-defined criteria and historical data, attractive properties and locations for rental, sale or project development are identified and a "score" for assessing their attractiveness is developed.

More Use Cases

Handwritten documents can be read out and prefilled using machine learning algorithms. By further input, these documents can be edited again, which again benefits the accuracy of the algorithm.

Electronic patient records can be evaluated using machine learning algorithms. This automatically provides doctors with suggestions for diagnoses and therapy options.

Diagnostic suggestions can be made by analyzing X-ray or MRI images using an algorithm.

Companies working with thousands of customers and suppliers need to categorize their documents so that requests can be handled in time.

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