Wherobots

Spatial data engines haven't kept up with the workloads being thrown at them. We fixed that. WherobotsDB next-gen is now GA: 3x faster queries, 46% lower cost than the next best alternative. Full benchmarks + free trial: bit.ly/4up1l5O

The biggest bottleneck in geospatial AI isn't the model architecture, it's data readiness. Join us for a hands-on session showing how to build automated pipelines that ingest, clean, and vectorize overhead imagery for immediate analysis. bit.ly/4r3AN7j

For 20 years, the answer to “Where should we store location data?” was PostGIS. The one-size-fits-all database is no longer enough. Learn how PostGIS, Wherobots and spatial data lakehouse fits together to meet today's needs without compromising cost. bit.ly/4bjtzGH

Geospatial data is shedding the "opaque blob" status. 🌍 Native support in Apache Parquet means geometry is now a first-class citizen in the columnar storage layer, no more workarounds for large-scale analytics. Read the breakdown: bit.ly/4kSNNLN

Raw satellite pixels ≠ AI insights. Data engineering makes the difference. In our “Getting Started” series, we’ll show you how to prepare geospatial data for large-scale change detection with RasterFlow. Join us: bit.ly/4kJJoKN

It takes 15 minutes for the Caltrain to get from Sunnyvale to San Jose. That’s how long it took the Wherobots MCP server to answer: “How many bus stops are in Maryland?” AI enables non-experts to use natural language to get insights in minutes. Full story: bit.ly/46X9G6A

We’re partnering with Felt to help data teams build solutions with spatial data and move beyond legacy GIS to adopt a modern spatial intelligence stack. Cloud-scale spatial processing meets collaborative, browser-based mapping. bit.ly/4krNS8N

Scaling spatial proximity analysis? The real bottleneck isn’t compute. It’s spatial density. Find out how KNN solves the spatial density problem for large-scale proximity analysis. bit.ly/45NPFit

Join AWS, Felt, and Wherobots tomorrow at 8AM PT as we discuss how geospatial AI and cloud solutions are reshaping agribusinesses and enhancing agricultural operations. Don’t miss the live session here: bit.ly/4rsj9KX

Ever open a spatial dataset and think, “I have no idea what’s in here”? The Wherobots Model Context Protocol (MCP) Server changes that. It helps you go from raw spatial data to production-ready analysis in minutes. Learn more in our upcoming office hour: bit.ly/45vJZJY

In 2025, we focused on getting the fundamentals of spatial data right. Performance, cost, reliability, and ease of use. Now, we’re building on that foundation to bridge AI with data from the physical world. High level recap and where we're headed next: bit.ly/4a20zm3

Before RasterFlow, teams building geospatial and satellite imagery pipelines relied on platforms like Google Earth Engine or invested in complex custom infrastructure to ingest raster data, preprocess imagery, and run machine learning models. RasterFlow changes that.

Join us and @Astronomerio for an interactive, hands-on workshop that takes you from raw data to a dynamic geospatial visualization. Learn how to orchestrate scalable data pipelines using Apache Airflow and WherobotsDB. Sign up here: bit.ly/3NqGqP1

With Wherobots Cloud Model Context Protocol (MCP) Server, you can now connect AI assistants like directly to your spatial data for catalog exploration, data quality checks, and geospatial query help—right from your dev environment. Full demo here: bit.ly/4jBaza8

Build production-grade geospatial data pipelines in 5 weeks! Learn ingestion, transformations, spatial joins, tiling, and AI-powered feature engineering with Sedona and Wherobots. Course starts Feb 3. 👉 Enroll now: bit.ly/4qk9Exu

Geospatial data breaks conventional data engineering. Learn how to adapt the medallion architecture for spatial workloads and how Iceberg and cloud-native formats like GeoParquet and COG, enable scalable spatial intelligence. bit.ly/4qb1S8X

When out on the console there arose such a cheer The MCP Server Public Preview is finally here! A gift for geo wizards and LLMs alike, Who speak plain English but think spatially precise. bit.ly/4qk09xO

Looking to run geospatial ML models at scale on satellite and aerial imagery? You’re invited to try RasterFlow and help shape the future of our product. Sign up for the private preview: bit.ly/3KUCYuX

How is geospatial analytics changing? We’re seeing a shift from piecing together fragmented tools to using fully formed, mature solutions. Hear how AI is making an impact and what all this means for future of geospatial. bit.ly/4rUZDIq

We’re excited to launch RasterFlow, a planetary scale inference engine for Earth Intelligence that takes insights and embeddings from satellite and overhead imagery datasets into Apache Iceberg tables, with ease and efficiency at any scale. bit.ly/3KP40Ux