Learning Wherobots by Building a National AI Data Center Suitability Report

This guest post is from a Wherobots user George Chandeep Corea, which covers an exploration of how he used Wherobots MCP with his preferred AI coding tools to build the interactive AI data center site suitability analysis tool below. The following quote is from his own biography. Learning by Doing Below is a working national […]

How Bad Telemetry Data Sabotages Modern Fleets

By the Teams at Action Engine & Wherobots Fleet monitoring is undergoing a generational shift. Fleet monitoring, the systems that ingest and analyze vehicle telemetry to track fleet health, performance, and safety, has become the foundation of how operators run vehicles, not just track them. Modern vehicles generate orders of magnitude more telemetry than even […]

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.

How Aarden.ai Scaled Spatial Intelligence 300× Faster for Land Investments with Wherobots

When Aarden.ai emerged from stealth recently with $4M in funding to “empower landowners in data center and renewable energy deals,” the company joined a new wave of data and AI startups reimagining how physical-world data drives modern business. Their mission: help institutional land investors rapidly evaluate the value and  potential uses of land across the country. […]

Advancing the Integration of Map Data via Overture’s Global Entity Reference System and Wherobots

The general availability of Overture’s Global Entity Reference System (GERS) makes it a lot easier to build intelligence about features of our physical world. 

Wherobots 2024 accomplishments, and what’s on-deck in 2025

2024 was a transformative year for Wherobots. Our mission to revolutionize how geospatial data is used took significant strides forward, positively impacting our customers and industry. Over the past year, we more than tripled the size of our team and successfully closed a $21.5M Series A funding round. We expanded accessibility to Wherobots’ industry-leading geospatial query performance, integrated Wherobots into the native AWS buying experience, and unveiled groundbreaking features like Raster Inference, Map Matching, and GeoStats—empowering users to create scalable geospatial solutions like never before.

Accelerating Vector and Raster Analysis at GeoPostcodes

How long is too long to wait for a data set to process? In the fast-paced world of data as a service, efficiency isn't just a nice-to-have; it's essential. But for GeoPostcodes, previous updates to the global population movement datasets took about 39 days. This was running on a headless QGIS instance in combination with PostGIS, combining population rasters with postal code boundaries.