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Introduction to Wherobots

Wherobots is a cloud-native analytics and ETL platform, purpose-built for creating data products and deriving answers from spatial data.

Wherobots enables geospatial data processing from local to planetary-scale.

Have you tried a Wherobots Onboarding Notebook?

Do you know how to:

  • Login to Wherobots Cloud...?
  • Load your vector data...?
  • Load your raster data...?
  • Perform Zonal Statistics on your raster data...?
  • Visualize your results...?

If not, good news! 🎉

Our Onboarding Series will get you started with all of these tasks in 3 steps:

  1. Register for a free Community Edition Organization.
  2. Start a Tiny runtime.
  3. Open our Welcome to Wherobots! Notebook at /examples/Getting_Started/Part_1_Loading_Data.ipynb.

Register Login

Unlocking the Value of Spatial Data

Wherobots empowers its customers to tackle geospatial opportunities by offering the following:

  • Continuous Production of Spatial Data Products - Wherobots is ideal for powering maps, APIs, or other geospatial data products that demand substantial computational capabilities.
  • Computer Vision on Remote Sensing Data - Wherobots enables advanced analysis such as segmentation, change and object detection from satellite imagery, land type classification, and climate analytics.
  • Risk or Opportunity Analysis - Wherobots facilitates sophisticated modeling for floodplains, natural disasters, and other location-based planning scenarios.
  • Space and Time Optimization - Wherobots helps you address geospatial decision-making such as, surfacing optimal land development locations, finding the most efficient transportation routes, and evaluating property acquisition and divestment targets.

What can Wherobots do for me today?

Wherobots empowers data teams to unlock the full potential of their spatial data by simplifying the development of geospatial solutions.
Wherobots offers:

  • Geospatial-focused developer tools designed to accelerate engineering productivity.
  • Industry leading spatial analytics, performance, and scale.
  • Cloud-native spatial ETL methods, analytics, and artificial intelligence.
  • A secure, serverless architecture.
  • Compatibility with Apache Sedona.
  • The flexibility to bring your own cloud storage.
  • Unified analytics across vector and raster data.
  • Support for building with Spatial SQL, Python, and Scala.