Geolava
Geolava is a spatial AI company that builds a world model for the built environment, turning aerial imagery and other observations into predictions of physical failure before it occurs. Its Terra model analyzes how assets change over time, enabling users to query everything from skylight leak risks to bridge bearing failure timelines. The platform is available through an institutional workbench interface or an API for custom deployment.
- Artificial Intelligence
- Property Technology
- Data & Analytics
- Software Only
- Enterprise Software
- Government Technology
Funding
Raised to date
$4.3MRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
across 2 rounds
EVST$4.3M · Seed
Announced Jul 2025
Disclosed cumulative: $4.3M
Founders
Product
Problem
Traditional property assessments require costly and time-consuming physical inspections, limiting the frequency and scope of evaluations across large portfolios or jurisdictions. This reliance on manual processes hinders real-time monitoring of property conditions and compliance with local regulations.
Solution
Geolava provides a spatial AI platform that leverages aerial imagery and visual feature recognition to deliver real-time insights into property conditions and regulatory compliance. The platform indexes property data and translates visual and location data into actionable intelligence, eliminating the need for on-site visits. Its core model, Terra, is a world model for the built environment that learns how the physical world changes to predict consequential physical change before it becomes physical failure. Users can query the model for specific predictions, such as identifying that an adjacent tower construction could reduce property valuation by up to 18% or that a bridge will experience critical bearing failure within 14 months. The platform delivers results through an institutional workbench for analysts and decision teams, or via API for custom integration.
Target Audience
Geolava's primary customers are organizations that manage large property portfolios or critical physical infrastructure, including real estate investment firms, insurance companies, government transit agencies, and defense logistics operations that require predictive failure analysis.
Features
- Visual feature recognition for automated property condition assessments
- Causal engine that detects hidden failure signals beyond standard inspections, predicting specific failure horizons (e.g., 14 months for bridge bearing failure)
- Multi-dimensional scenario analysis, such as assessing the impact of proposed construction on property valuation or increased freight traffic on bridge safety
- Workbench Access, an institutional interface for analysts, operators, and decision teams to query the live world model
- Infrastructure Access offering usage-based model inference, live state embeddings, and private deployment inside institutional systems
- API and model integration for building custom solutions