Planetary-scale answers, unlocked.
A Hands-On Guide for Working with Large-Scale Spatial Data. Learn more.
I'm a Staff Product Manager at Wherobots, responsible for RasterFlow. My background is in technical enterprise product management with a focus on geospatial analytics, with previous experience at Oracle, HERE Technologies, and Kinetica.
RasterFlow Public Preview: Planetary-Scale Earth Intelligence with Predictable Pricing
We are excited to announce that RasterFlow is now in Public Preview, opening up the power of planetary scale Earth Intelligence to all Wherobots Professional Edition customers! RasterFlow let’s you solve complex monitoring challenges with vision-language models or tailored models for specific use cases, without needing to manage complex inference infrastructure. Teams are already running […]
How well does SAM3 detect building footprints? We asked the Wherobots Spatial AI Coding Assistant
In a recent post, we showed how easy it is to use RasterFlow and Meta’s Segment Anything 3 Model (SAM3) to detect features in the physical world. A single end-to-end pipeline built a 133 GB NAIP mosaic of Marion County, Oregon, ran SAM3 against it with text prompts spanning eight classes, and produced approximately one […]
Introducing RasterFlow: a planetary scale inference engine for Earth Intelligence
RasterFlow takes insights and embeddings from satellite and overhead imagery datasets into Apache Iceberg tables, with ease and efficiency at any scale.
Introducing Scalability for GeoPandas in Apache Sedona
Learn about the new GeoPandas API for Apache Sedona, now available in Wherobots. This new API allows GeoPandas developers to seamlessly scale their analysis beyond what a single compute instance can provide, unlocking insights from large-scale datasets. This integration combines the Pythonic GeoPandas API with the distributed processing power of Apache Sedona.
