⚡ Powered by DuckDB · Rust · FlockMTL

Query Any Geospatial Data,
Anywhere in the Cloud

GeoQ Cloud Native is a proprietary CLI & web platform for querying LAZ point clouds, GeoTIFF rasters, and vector datasets from local storage, S3, GCS, or any HTTP endpoint — all with a single binary.

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$ geoq cloud point-cloud --source s3://lidar-bucket/city.copc.laz --bbox "-122.5,37.7,-122.3,37.9" --output csv
classification,intensity,x,y,z,count
2,847,−122.41,37.81,12.4,14293
6,1204,−122.43,37.79,142.1,3841

$ geoq cloud stac search --url https://earth-search.aws.element84.com/v1 --collection sentinel-2-l2a --bbox "-122.5,37.7,-122.3,37.9"
✓ 12 items found · cloud_cover avg 4.2% · 2024-01-01 → 2024-06-30

$ geoq cloud vector --source data.fgb --sql "SELECT name, population FROM features WHERE population > 1000000" --output geojson
✓ 8 features exported · 2.3 MB · 0.41s
10+
Data Format Readers
3
Cloud Providers
12+
API Integrations
1
Binary, Zero Deps
AI
Natural Language Queries
Core Capabilities

Everything Geospatial, One Tool

From raw point clouds to AI-powered map exploration — GeoQ handles every layer of the modern geospatial stack.

☁️
Cloud-Native Storage
Direct HTTP range requests against S3, GCS, and any HTTPS endpoint. No download needed — query petabytes in place with DuckDB httpfs and AWS credential chain support.
S3GCSHTTPRange Requests
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🌩️
LiDAR Point Clouds
Read LAZ 1.4 and COPC files via the DuckDB PDAL extension. Spatial bbox filters, classification queries, intensity histograms — all in SQL, locally or from S3.
LAZ 1.4COPCPDAL3D Viz
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🗺️
Raster & COG
Query GeoTIFF and Cloud-Optimized GeoTIFFs with band selection, pixel statistics, and reprojection. Renders live in the web UI via ArcGIS ImageryTileLayer.
GeoTIFFCOGBand QueryArcGIS
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📐
Vector Formats
Read FlatGeobuf, GeoParquet, GeoJSON, and KML through DuckDB spatial. Run arbitrary SQL with spatial functions against any source.
FlatGeobufGeoParquetGeoJSONKML
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🤖
AI Natural Language Queries
Ask questions in plain English. The FlockMTL + OpenAI agent translates your intent into SQL, executes it, and returns analyst-friendly summaries with map results.
FlockMTLOpenAINL→SQL
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🔗
Rich API Integrations
STAC, ArcGIS FeatureServer/ImageServer, OGC API Features (CQL2), SensorThings, OpenSearch EO, CKAN, CSW, Socrata, PostGIS — all in one CLI.
STACOGCArcGISCKAN
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Architecture

One Engine, Two Interfaces

A shared Rust engine powers both the CLI and the web API. DuckDB handles all data access — extensions load on demand.

💻
CLI User
geoq cloud …
→
⚡
geoq-engine
Rust · DuckDB
→
🦆
DuckDB
spatial · httpfs · pdal
→
☁️
Data Sources
Local · S3 · GCS · HTTP
🌐
Web User
Next.js frontend
→
🦀
geoq-web
Axum · REST API
→
🤖
AI Agent
FlockMTL · OpenAI
→
🗺️
Map + 3D View
ArcGIS · Three.js
Built On

Best-in-Class Technology Stack

GeoQ stands on proven, production-grade technologies — no proprietary lock-in.

Rust DuckDB PDAL (Point Clouds) DuckDB Spatial httpfs (S3 · GCS) FlockMTL AI OpenAI Axum (HTTP) Next.js 15 ArcGIS JS SDK 5 Three.js (3D) copc.js (COPC) GeoParquet FlatGeobuf PostGIS STAC API
Output Formats

Export Anywhere

Results flow out in the format your downstream tools expect — no conversion step required. GeoJSON feeds directly into web maps. GeoParquet and CSV go straight into Pandas or Spark. LAZ output stays in the cloud-native COPC hierarchy.

GeoJSONCSVParquet GeoParquetFlatGeobuf LAZGeoTIFFKML
# Export as GeoJSON
geoq cloud vector --source data.fgb --output geojson

# Export as GeoParquet
geoq cloud stac query --collection sentinel-2-l2a --output parquet --out-file results.parquet

# Export LAZ point cloud filtered
geoq cloud point-cloud --source city.copc.laz --bbox "-122.5,37.7,-122.3,37.9" --output laz

Start Querying the Earth — Right Now

A single cargo build --release gives you everything: CLI, web API, and the AI agent.

Request Access → See AI Chat Demo