Wherobots

The Spatial Intelligence Cloud for Planetary-Scale Analytics and AI

Freemium

Description

Wherobots provides a comprehensive cloud platform engineered for handling spatial data operations at a massive scale. Developed by the original creators of Apache Sedona, it addresses the challenges organizations face with legacy solutions and general-purpose data lakehouses by offering specialized tools for geospatial workloads. The platform facilitates seamless spatial joins, efficient data filtering through spatial context, and AI-driven analytics to uncover meaningful patterns within geographic data.

Leveraging a modern lakehouse architecture, Wherobots enables data teams to build and deploy scalable spatial ETL and analytics pipelines using familiar tools like SQL and Python. It integrates various components, including Wherobots Cloud for managing resources, Wherobots Spatial Catalog for data asset management, WherobotsDB as the core analytics engine, and WherobotsAI for processing aerial imagery. This suite helps translate complex spatial analytics into actionable strategic decisions for businesses.

Key Features

Wherobots Cloud: A cloud computing platform for spatial analytics and AI needs, managing resources and supporting SQL/Python workloads.
Wherobots Spatial Catalog: A spatial data assets library for discovering, managing, and sharing geospatial data products.
WherobotsDB: A scalable spatial data engine based on Apache Sedona for spatial ETL and analytics.
WherobotsAI: An inference engine for identifying and classifying features from satellite and aerial imagery using AI within SQL.
Spatial Joins: Seamlessly link datasets based on geographic locations.
Spatial Queries: Clean, filter, and slice data using spatial context.
AI-driven Analytics: Employ AI to discover meaningful patterns and trends in spatial data.
Isochrones Functions: Enhance location intelligence based on travel time.
Apache Sedona Integration: Built by the creators of Apache Sedona for processing spatial data at scale.

Use Cases

Performing spatial ETL (Extract, Transform, Load) operations at scale.
Conducting large-scale spatial analytics.
Developing AI models for Earth Observation data.
Analyzing aerial and satellite imagery.
Optimizing location-based decisions using travel time (isochrones).
Cleaning and enhancing mobility data (e.g., GPS data).
Building spatial data pipelines for production workloads.
Managing and discovering spatial data assets.

Frequently Asked Questions

What are Spatial Units and how much do they cost?

A Spatial Unit (SU) is an amount of computational horsepower provisioned to a serverless runtime, providing similar capacity as a 32vCPU Apache Sedona cluster. Costs per SU are $1.50 in AWS US West (Oregon) and $1.67 in AWS EU West (Ireland).