Welcome
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Welcome to Geolava, your Spatial AI as a Service platform. Our mission is to bring powerful spatial intelligence to the physical world, enabling you to seamlessly analyze and manage real-world assets, starting with properties.
Geolava goes beyond just optical imagery. We integrate data from SAR (Synthetic Aperture Radar), LiDAR, Spectral, Thermal, and traditional overhead/street-level sources into a single, unified embedding. This allows us to model the 3D structure of properties, detect hidden features (e.g., moisture behind walls using thermal signatures), and handle complex phenomena like vegetation or rooftop solar arrays via spectral analysis. Our advanced embedding, updated regularly, ensures each property’s location and context is represented in a way that powers sophisticated insights.
Rather than forcing you to build everything from scratch, Geolava offers a family of pre-trained Agents that tackle common real estate problems:
Valuation – Real-time property price estimates
Condition – Structural and environmental health
Compliance – Permitting and zoning checks
Attribute Search – Custom filtering (e.g., “properties with graffiti”)
Monitoring – Continuous tracking for event-based alerts
These Agents abstract away the complexity of in-person assessment or multiple data ingestions, so you can simply call a specific Agent for immediate, domain-targeted answers.
For specialized needs, you’ll soon be able to create custom Agents that integrate your own rules, data sources, or labeling. Whether you’re in insurance, government, or niche enterprise, this feature will allow you to adapt Geolava’s Spatial AI capabilities to your unique processes.
You can query individual addresses or property IDs.
You can also specify broader regions, such as cities, states, or bounding boxes, and Geolava will process every covered property in that region.
For enterprise scenarios, upload your own dataset (such as a CSV or JSON with hundreds or thousands of properties). Our API endpoints can process these properties in bulk, returning results for each one.
