Spatial Intelligence for Aerospace Process petabytes of satellite imagery and sensor data up to 20x faster. Transform your Earth observation workflows with cloud-native geospatial analytics built for the modern aerospace industry REQUEST A DEMO Companies Accelerating Outcomes with Wherobots and Apache Sedona why wherobots for Aerospace & EO Process petabytes, eliminate bottlenecks, and experience a complete data stack for Earth Intelligence. Overwhelming data volumes Detection bottlenecks Preprocessing delays Fragmented analytics stack Multi-sensor data integration Overwhelming data volumes Industry Problem Overwhelming data volumes Aerospace and EO companies manage 100+ petabyte archives growing by 80-100TB daily, while traditional processing pipelines create bottlenecks that delay insights from satellite imagery by hours or days Wherobots solution Planetary-scale processing Handle petabyte-scale satellite imagery archives with distributed processing that scales automatically. Wherobots processes massive raster and vector datasets across your entire constellation without infrastructure management 100+ PB Processing Capacity Detection bottlenecks Industry Problem Change detection bottlenecks Monitoring environmental changes, infrastructure development, or disaster impacts requires comparing billions of pixels across time, computations that overwhelm traditional GIS systems Wherobots solution Distributed change detection Execute pixel-level change detection and semantic segmentation across global imagery stacks. Leverage distributed computing to identify land cover changes, deforestation, and infrastructure development at continental or planetary scale 10× Faster Analysis Speed Preprocessing delays Industry Problem Preprocessing delays Raw satellite data requires atmospheric correction, orthorectification, radiometric calibration, and cloud masking before analysis, creating processing pipelines that take days to deliver analysis-ready data Wherobots solution Streamlined data preparation Build efficient ETL pipelines for satellite imagery preprocessing using distributed Spatial SQL and Python. Transform raw imagery to analysis-ready data at scale with minimal configuration ETL Time Days → Min Fragmented analytics stack Industry Problem Fragmented analytics stack EO teams juggle multiple tools for raster processing, vector analysis, machine learning inference, and data cataloging creating complexity and integration overhead Wherobots solution Unified geospatial platform Combine raster and vector processing, spatial analytics, and ML inference in a single environment. WherobotsAI runs computer vision models on satellite imagery using simple SQL commands for feature detection and classification 1 Platform Tools Unified Multi-sensor data integration Industry Problem Multi-sensor data integration is difficult Aerospace systems generate diverse data from aircraft sensors, navigation systems, and satellite constellations in varying formats that are difficult to integrate and analyze together Wherobots solution Multi-format data integration made easy Process and join data from multiple satellites, sensors, and formats. Wherobots Spatial Catalog provides a unified view of all geospatial datasets with Apache Iceberg-based data lakehouse architecture 50+ Formats Unified “The combination of speed, scalability, and ease of integration has boosted our engineering productivity and will accelerate how quickly we can deliver new geospatial data products to market.” Rashmit Singh CTO & Co-founder, SatSure Unleash Developer Productivity in Aerospace Teams Schedule a demo to see how leading insurers process billions of location records and work with raster and vector data in the same platform. Request Demo Explore Our Resources Get up to speed on the latest innovations in Aerospace. Raster data joins at scale Compare Wherobots with google Earth Engine and Big Query for raster operations, joins at scale, and running EO models. LEARN MORE Introducing RasterFlow on Wherobots RasterFlow is a serverless image preparation and inference engine that makes it significantly easier to generate Earth Intelligence from planetary scale Earth Observation (EO) datasets. Learn More Webinar: Introducing RasterFlow for Planetary Scale Earth Intelligence How RasterFlow works and why you should consider it for planetary-scale EO models that you want to run instantly. RasterFlow Webinar FAQ How does Wherobots handle petabyte-scale satellite imagery archives? Wherobots leverages a modern data lakehouse architecture built on Apache Iceberg and cloud object storage. Your imagery stays in cost-effective cloud storage while WherobotsDB provides distributed query processing. The platform scales automatically to handle queries across petabytes of data, and you only pay for compute when processing jobs run. What are the typical deployment options for Wherobots for aerospace companies? We deploy as a managed cloud service. But we also have options for bring-your-own-cloud and VPC. Can Wherobots process both raster imagery and vector geospatial data? Yes. Wherobots provides unified support for both raster and vector geospatial data in a single platform. WherobotsDB includes over 300 spatial functions covering geometry operations, raster analytics, and spatial joins. You can combine vector map data with satellite imagery analysis in the same SQL query or Python workflow, eliminating the need for multiple specialized tools. How does WherobotsAI help with satellite imagery analysis? WherobotsAI provides a “bring your own model” inference engine that runs computer vision models on satellite imagery at scale. You can perform object detection, semantic segmentation, and classification directly from SQL or Python without managing GPU clusters. For example, you can write a query to detect buildings, roads, or land cover types across millions of images, and Wherobots handles distributed model inference automatically. What makes Wherobots faster than traditional aerospace and Earth observation processing pipelines? Wherobots incorporates multiple performance optimizations: proprietary spatial indexing techniques, query optimization for geospatial operations, distributed parallel processing, and efficient I/O with cloud storage. These deliver up to 20x faster execution compared to processing the same workloads with general-purpose data platforms. Faster processing means quicker time-to-insight and lower compute costs. Does Wherobots work with our existing aerospace data infrastructure? Yes. Wherobots integrates with cloud data platforms including AWS, and can connect to data warehouses like Snowflake and Databricks. The platform is built on Apache Sedona APIs, providing compatibility with standard geospatial workflows. You can start with a subset of your data for pilot projects while keeping existing systems operational. Get started Ready to transform your aerospace workflows? Request Demo
Raster data joins at scale Compare Wherobots with google Earth Engine and Big Query for raster operations, joins at scale, and running EO models. LEARN MORE
Introducing RasterFlow on Wherobots RasterFlow is a serverless image preparation and inference engine that makes it significantly easier to generate Earth Intelligence from planetary scale Earth Observation (EO) datasets. Learn More
Webinar: Introducing RasterFlow for Planetary Scale Earth Intelligence How RasterFlow works and why you should consider it for planetary-scale EO models that you want to run instantly. RasterFlow Webinar
