• VRnow

    VRnow is a Berlin-based PropTech startup with a global reach, focusing on the digitalization of real estate properties for more transparency, a greater degree of predictability and better visualizations. Our clients are property holders, developers and real estate agencies.

  • Artificial Intelligence

    Any technique that enables computers to mimic human intelligence

    Machine Learning

    A subset of artificial intelligence

    Machine learning uses complex statistical techniques that enable machines to improve at tasks with experience. This includes the category of deep learning.

    Deep Learning

    A subset of machine learning

    Deep learning is based on algorithms that enable software to train itself to perform certain tasks, such as speech and image recognition, by exposing multilayered neural networks to vast amounts of data.

  • Our technology

    By introducing deep learning into the subfield of Floor Plan Analysis, VRnow is establishing a new state of the art. Deep learning excels in image classification, and is used by large companies such as Facebook and Google. VRnow uses this technique to extract structural and semantic details like walls, windows, doors and furniture from blueprints. The extracted information can then be used and interpreted according to the client's needs. Using this digital process, VRnow can then automatically create a sophisticated 3D environment. Our concept is based on more transparency, a greater degree of predictability and better visualization of real estate objects.

  • Different steps:

    Transparency, Predictability, Visualization

    Transparency

    Extraction of architectural information

    Step 1 is the extraction of architectural information from a floor plan. Using the Floor Plan Analysis, it is possible for our algorithm to detect various information such as the size of the property and the number of doors, windows or rooms.

    Predictability

    Result and analysis

    Step 2 is the result and analysis based on the extracted architectural information. The information gained can improve further strategic planning and facilitate cost calculation and furnishing set-ups. Deep learning is at the core of our algorithm; the more data it gets, the smarter the algorithm will become and the more it can improve the quality of the product. In the future, we may go on not only to analyze energy costs but also to create indoor navigation systems for large facilities.

    Visualization

    360° video and 3D models

    Step 3 is the automatic creation of a 3D model from any given floor plan. The visualized object can then be accessed using VR gear, YouTube 360 (for a 360° video) or a browser.

  • Multi-Platform Development

  • The team

    Tim Meger-Guingamp

    CEO & Co-Founder

    Alexander Dolokov

    CTO & Co-Founder

    Matthias Renneke

    CTO

    Paul Smoletz

    CSO

    Sebastian Rummler

    Management Assistant

    Martin Wirtig

    3D Artist

    Julian-Alexander Hoff

    3D Artist

    Johannes Holweg

    Unreal Developer

    Malte Koch

    Developer

    Manon Meger

    Office Manager

    Hannes Heller

    Intern

    Justin Schulz

    Intern

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