Planetary-scale answers, unlocked.
A Hands-On Guide for Working with Large-Scale Spatial Data. Learn more.
You can now use Databricks for geospatial with Wherobots.
Authors
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.
Before founding Wherobots, co-founders Mo and Jia identified critical challenges limiting the potential of geospatial data. These stemmed from how geospatial data was traditionally stored, formatted, and processed, and made this data incredibly painful to utilize, particularly at scale.
Over the recent decades, data and analytics investment was mostly directed towards solutions for internet data. However compared to internet data, geospatial data is a lot more complex, which makes it harder to query. It’s polygons representing land and buildings, GPS trajectories, satellite and drone imagery, weather data, and more—all tied to Earth’s imperfect spherical surface. And querying this data generally means you need to filter and join it with other datasets (geo or non-geo). Due to this complexity, existing cloud analytics engines built for structured internet data struggle to efficiently run spatial queries at scale. They also miss features necessary to prepare this data, they lack features that make solution development productive, and simply cannot compute spatial results with high precision. As a result, solutions based on geospatial data are expensive, or otherwise shelved.
We are addressing these challenges. By reducing the cost and effort to build with geospatial data, Wherobots will enable a new wave of innovation for the physical world. This will drive breakthroughs in products, business operations, science, government, and make a positive impact on our climate.
Our mission is simple yet ambitious: make geospatial data easy to use.
Here’s what some of our customers have to say about how we’re helping them achieve their missions.
Enabling insurers to calculate geographic risk with precision
“Wherobots runs our compute operations that used to take hours or days to complete, in minutes. As we provide perils information (flood, fire, etc) to insurers at the property level, we particularly appreciate the ability to be able to run combined vector/raster analysis, without having to previously transform the raster data into vector format or some other format.” – John Powell, Senior Geospatial Data Engineer at AddressCloud
Creating next-generation map products with scalable, open map data
“Overture produces a building dataset covering all buildings in the world, with 2.3B geometries and growing, that’s updated frequently. There’s a lot of data and compute that goes into producing and keeping it up to date,” said Jennings Anderson, Geoscientist at Overture and Data Engineer at Meta. “We accelerated the pipelines that produce the buildings dataset by up to 20x after we moved them to Wherobots, which required a simple redirection of our code. We retained compatibility with Apache Sedona, and the move put us into a development experience that’s made us more productive.” – Jennings Anderson, Geoscientist at Overture and Data Engineer at Meta
Several recurring themes highlight why customers choose Wherobots:
Unmatched performance and cost efficiency: Wherobots delivers up to 20x better spatial join performance compared to modern cloud data engines, at a fraction of the cost.
Ease of innovation: Wherobots makes it easy to build solutions with raster (e.g., satellite imagery), vector (e.g., geometry, geography) data, and your first party data regardless of scale.
Modern cloud architecture: Wherobots is fully compatible with Apache Sedona, and runs seamlessly on data lakes with support for Apache Iceberg and Apache Parquet.
In 2024, we raised $21.5M in a Series A round led by Felicis, with support from Wing Venture Capital, Clear Ventures, JetBlue Ventures, and P7 Ventures. This funding reflects confidence in our mission and the massive market opportunity for geospatial solutions in the cloud.
The Wherobots team—the “Botsters”—tripled in size this year. While engineering saw the most growth, we also built out go-to-market, marketing, and product teams and are actively scaling our sales team. As we head into 2025, we’re actively hiring for roles across the company to support our expanding vision.
We launched several key features in 2024 that expanded the boundaries of geospatial data solutions. *The features noted with an are only available in the professional or enterprise edition of Wherobots.****
Cloud Native
Security and Access
Open Data Architecture
Accelerating Geospatial Solution Development
Automation
In 2025, we plan to bring Wherobots Cloud to the EU market with support for the AWS Europe (Ireland) region, and achieve the SOC 2 Type 2 certification (currently in progress). We’ll continue to focus on:
We are currently offering a 30-day free trial covering up to $400 in usage via the AWS Marketplace. Getting started is easy. There are many example notebooks for various geospatial use cases that you can explore and run without any coding experience required. Not only do the notebooks help you get started, but we also see most of our customers use these notebooks as references for the solutions they end up building.
Motivated by our mission? Join our growing team—visit our careers page for open roles. You can also share feedback at feedback@wherobots.com or contact me directly at damian@wherobots.com.
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.
Wherobots and Taylor Geospatial Engine Bring Fields-of-the-World Models to Production Scale
Agriculture depends on timely, reliable insight into what’s happening on the ground—what’s being planted, what’s being harvested, and how fields evolve over time. The Fields of The World (FTW) project was created to support exactly this mission, by building a fully open ecosystem of labeled data, software, standards and models to create a reliable global […]
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. […]
share this article
Awesome that you’d like to share our articles. Where would you like to share it to: