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Google > Case Studies > Syte: Helping to Bring New Housing to Market with the Speed of AI

Syte: Helping to Bring New Housing to Market with the Speed of AI

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Customer Company Size
Startup
Region
  • Europe
Country
  • Germany
Product
  • Google Cloud
  • BigQuery
  • Google Kubernetes Engine (GKE)
  • Compute Engine
Tech Stack
  • Google Cloud
  • BigQuery
  • Google Kubernetes Engine (GKE)
  • Compute Engine
Implementation Scale
  • Enterprise-wide Deployment
Impact Metrics
  • Productivity Improvements
  • Digital Expertise
  • Environmental Impact Reduction
Technology Category
  • Analytics & Modeling - Predictive Analytics
  • Platform as a Service (PaaS) - Data Management Platforms
  • Infrastructure as a Service (IaaS) - Cloud Computing
Applicable Functions
  • Business Operation
Use Cases
  • Building Energy Management
  • Remote Asset Management
Services
  • Cloud Planning, Design & Implementation Services
  • Software Design & Engineering Services
  • System Integration
About The Customer
Syte is a German property tech startup that is revolutionizing the real estate industry with its AI-driven platform. The company provides real-time access to relevant property data, enabling real estate developers, investors, and architects to quickly assess the building potential of properties. Syte's platform helps optimize energy consumption and facilitates the re-densification of existing buildings to create additional housing space. Founded by David Nellessen and Matthias Zühlke, Syte aims to address the housing shortage in Germany by streamlining the process of property development and expansion. The company leverages advanced technologies, including Google Cloud tools, to enhance its data processing capabilities and improve the efficiency of real estate development.
The Challenge
Germany is facing a significant housing shortage, with a deficit of 700,000 homes. The cost of building materials is rising, rents are increasing, and incomes are being squeezed by the cost of living. Re-densification, which involves redeveloping and adding stories to existing buildings, is seen as a potential solution. However, this process is complex and requires navigating numerous logistical challenges, such as building law compliance. Traditional methods for identifying suitable sites for re-densification are time-consuming, often taking several days or weeks.
The Solution
Syte utilizes Google Cloud tools to enhance its AI-driven property platform, enabling real-time retrieval of property data. The platform allows users to search a database of 25 million properties using multiple filter parameters, significantly reducing the time required to identify sites for re-densification. By deploying BigQuery, Syte improved its search engine's scalability and responsiveness, reducing response times from 60 seconds to a maximum of two seconds. Additionally, Syte employs Google Kubernetes Engine (GKE) for training machine learning models, running data pipelines, and hosting web services. This setup has led to a 40% improvement in productivity by simplifying the deployment and management of applications. Compute Engine supports Syte's data processing needs, allowing the company to process massive amounts of LiDAR data efficiently. The integration of these technologies enables Syte to offer new features to larger target groups with minimal technical effort, focusing on reducing the carbon impact of the building sector.
Operational Impact
  • Syte's platform allows for real-time retrieval of property data, significantly reducing the time required to identify sites for re-densification.
  • The use of Google Cloud tools has improved the scalability and responsiveness of Syte's search engine, reducing response times to a maximum of two seconds.
  • Google Kubernetes Engine (GKE) has enhanced productivity by 40%, simplifying the deployment and management of applications.
  • Compute Engine enables efficient processing of massive amounts of LiDAR data, supporting Syte's data processing needs.
  • Syte can now integrate new features into its software with minimal technical effort, allowing the company to focus on reducing the carbon impact of the building sector.
Quantitative Benefit
  • Search response times reduced from 60 seconds to a maximum of two seconds.
  • Core data processing time reduced from a year to within a week.
  • Productivity in deploying web applications improved by approximately 40%.

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