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Unleash AI on physical world data.

The most capable cloud for physical AI and physical world data at any scale.

Start for free Explore Havasu Catalog
Wherobots Replay of a real Wherobots analysis
Searched the Havasu Catalog: Overture, Regrid, FEMA NRI + NFHL, USFS2.77M buildings · 2.72M parcels
Wrote spatial SQLWherobotsDB
SELECT r.peril, COUNT(DISTINCT b.id) AS buildings_exposed
FROM wherobots_open_data.overture_maps_foundation.buildings_building b
JOIN co_risk.parcels p ON ST_Intersects(b.geometry, p.geometry)
JOIN co_risk.peril_zones r ON ST_Intersects(b.geometry, r.geometry)
WHERE r.peril IN ('hail', 'wildfire', 'tornado', 'flood', 'wind')
GROUP BY r.peril ORDER BY buildings_exposed DESC
Ran the query: 5 perils rankedstatewide
2,172,394
Colorado buildings exposed to hail, 78.4% of the state. Hail leads wildfire.

Trusted by teams building with AI on physical-world data with Wherobots and Apache Sedona

Customer proof

We went from babysitting compute jobs for a week to getting results before lunch.

Why teams love Wherobots

Four challenges teams overcome building with physical world data.

These are the most commonly referenced reasons why our customers build their physical world data products with Wherobots.

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01

Velocity is slow

The problem

Ideas take weeks to months to ship.

  • Many never reach production at all
  • Bespoke infrastructure for every project
  • Unfamiliar data structures and silos
buildings × parcels+ elevation, slope9h 58mtimeout97%
With Wherobots

Test ideas in minutes, ship solutions in days.

  • Prototype to production on one platform
  • Managed compute, no infrastructure to build
  • Raster, vector and your tables in one query
buildings × parcels+ elevation, slopecompleteone query100%
02

Finding and preparing spatial data takes weeks

The problem

The right data is hard to find.

  • Hunting across data portals and vendor sites
  • Download, clean and reproject before any query
  • Repeat the search for every new project
.shp.tif.csv.gpkg.kmlEPSG:27700DAY30
With Wherobots

Query the right data in place from day one.

  • Overture, NAIP, Sentinel-2 and easy STAC collections
  • Schemas and sample SQL, ready to query in place
  • Next to your own tables, reused across projects
overture.buildingsopenoverture.placesopensentinel2.l2aopenyour_org.parcelsyoursDAY1
03

AI and teams can't use physical world data

The problem

Spatial engineering expertise is scarce.

  • Projections, spatial indexes and tiling
  • Hard-won knowledge locked in a few heads
  • Spatial code from general AI breaks on real data
SELECT ST_MagicJoin( a.geom, b.geom)FROM roads a, pts blat/lon swapped
With Wherobots

Expertise baked into every layer.

  • Projections, indexing and tiling handled for you
  • Familiar SQL and Python for everyone on the team
  • AI agents get spatial expertise through MCP
SELECT ST_Intersects( a.geom, b.geom)FROM your_catalog.roadsEPSG:4326
04

Handcuffed by tooling limitations and seat-based licensing

The problem

GIS lock-in or data platform gaps.

  • Legacy GIS lock-in and per-seat licenses
  • Data platforms that are incomplete for spatial work
  • Spatial is a side quest on their roadmaps
.gdb .lyrx .sdeper-seat licenserenewal
With Wherobots

Extend your data platform, pay on demand.

  • Open file and table formats, no per-seat licenses
  • Extends the data platform you already run
  • Spatial-first expertise, priced on demand
GeoParquet · COGno seat licensespay per job

Solutions by industry

See how your industry builds with Wherobots.

Physical world context for the teams that plan, insure, power and connect the world.

Talk to sales See all solutions

Aerospace & Earth observation

Satellite imagery analysis and geospatial AI inference at petabyte scale.

Energy & utilities

Wildfire risk, solar site selection and grid intelligence.

Financial services & insurance

Climate and property risk across millions of locations.

Mobility & map making

Billions of GPS points turned into location intelligence and maps.

Communication service providers

Network events, 5G planning and coverage analytics.

Sustainability & agriculture

Satellite crop monitoring and field boundary detection.

Open-source foundation

From the original creators of Apache Sedona.

Apache Sedona is the most widely deployed open-source distributed spatial engine in the world. The team that created it built Wherobots on the same foundation, so Wherobots is 100% compatible with existing Apache Sedona workloads: your Sedona code runs unchanged.

Explore Apache Sedona Compare Sedona and Wherobots
Downloads 80M+ Apache Sedona downloads
In production 20,000+ organizations run Sedona
Cover of the O'Reilly book Cloud Native Geospatial Analytics with Apache Sedona
O'Reilly book

Download the Apache Sedona book.

Cloud Native Geospatial Analytics with Apache Sedona: a hands-on guide to running Sedona locally and in the cloud, querying large geospatial datasets with spatial SQL, and applying machine learning to spatial data.

Download the book

Blog

Latest from Wherobots

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FAQ

Frequently asked questions

What is Wherobots?

Wherobots is a cloud platform for analyzing physical world data, built by the original creators of Apache Sedona. WherobotsDB runs spatial SQL and Python with 300+ vector and raster functions, RasterFlow turns satellite and aerial imagery into physical-world features, and the Havasu Catalog keeps open datasets next to your own.

Does Wherobots work with Databricks, Snowflake and AWS?

Yes. Wherobots reads data where it lives, including Databricks Unity Catalog, Snowflake Horizon Catalog, AWS Glue Catalog, Amazon S3 Tables and PostGIS, and writes results back in open formats such as Apache Iceberg and Delta Lake. See the Havasu Catalog for the datasets ready to query.

How fast is Wherobots?

Across SpatialBench at SF 1000, WherobotsDB runs spatial queries and joins 2.5x faster, with up to 45% better price-performance. Read the benchmark results.

What is the connection between Wherobots and Apache Sedona?

Wherobots was built by the team that created Apache Sedona, the open-source distributed spatial engine with 80M+ downloads. Wherobots is 100% compatible with existing Apache Sedona workloads, so your Sedona code runs unchanged. Compare Sedona and Wherobots.

Can I use Wherobots with AI coding tools?

Yes. The Spatial AI Coding Assistant brings spatial SQL to VS Code and Claude Code, and agents such as Claude, Cursor, ChatGPT and Codex, Devin or any MCP client can connect through the Wherobots MCP server. Read the AI coding tools docs.

How do I get started with Wherobots?

Start a free trial and test your first idea at $0, or talk to our team about your use case.

What is physical AI?

Physical AI is artificial intelligence that perceives, reasons about, and acts in the physical world, from robots and autonomous vehicles to models that read satellite, aerial, and sensor data. Read what physical AI is and the spatial data it runs on in our Discover guide.

Sphere

Run your first spatial query.

Create an account, and test your first idea at $0.

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