Python library with 9 data APIs, 100+ algorithms and 170+ accessor methods for geospatial analysis. Optimised for use with large language models – token consumption reduced by approximately 95% compared to manual implementations.
The Geospatial API is a specialised Python library that encapsulates complex geodata workflows into simple, token-efficient function calls. Instead of manually generating hundreds of lines of code, an AI model calls a single method – with standardised parameters and validated results.
The API is the technology foundation for all CRVA reports and is continuously improved through recursive optimisation: each benchmark run identifies improvement opportunities that feed into the next API version.
Buildings, roads, land use, POIs and infrastructure worldwide.
Sentinel-2 satellite imagery, land cover and vegetation indices.
Statistical data on population, economy and environment at EU level.
Active fire detection data and fire hotspots in real time.
German Weather Service data – historical and current.
Global soil properties at 250m resolution for environmental analysis.
Weather forecasts and historical climate data worldwide.
DWD weather data via an open JSON API.
AI-optimised web search for current information and context data.
Slope, aspect, terrain modelling and morphometric parameters.
Catchment areas, flow accumulation, drainage networks and flood modelling.
NDVI, EVI, NDWI and additional spectral indices from satellite imagery.
Temperature trends, precipitation patterns, extreme events and scenario evaluation.
Flood, drought, heat and storm risks with multi-hazard aggregation.
Hotspot analysis, clustering, spatial autocorrelation and interpolation.
Imperviousness, green space proportion, urban heat island effects.
Accessibility, network analysis, site assessment and service coverage.
Soil types, organic carbon, water storage capacity and erosion risk.
Image classification, change detection and multi-temporal analysis.
Reprojection, intersection, buffering and format conversion.
Automatic report generation, map export and data visualisation.
The Geospatial API is the technology foundation of our EU Taxonomy CRVA reports. All 33 climate hazards pursuant to EU Taxonomy are analysed via standardised API calls – from data retrieval through risk calculation to report generation.
By encapsulating complex workflows into validated function calls, the quality of every analysis becomes reproducible and auditable. Engineers use the API as a tool to conduct location-specific climate risk analyses efficiently and consistently.
The Geospatial API enables the automation of complex multi-step geodata workflows. Instead of manually orchestrating individual processing steps, you define the desired workflow – the API handles data retrieval, processing, validation and result preparation.
Typical use cases include automatic site analysis for real estate portfolios, batch processing of climate risk analyses for banks and insurers, and integration of geodata into existing reporting and risk management pipelines.
The Geospatial API is improved through a continuous optimisation cycle: each benchmark run identifies where AI models reach their limits or produce suboptimal results. These insights feed directly into the next API version.
The result: algorithms become more precise, default values better calibrated, token consumption further reduced. Each new version of the API automatically improves the quality of all analyses built upon it – including the CRVA reports.
The algorithms and data sources of the Geospatial API are designed to meet the requirements of European regulatory frameworks. All relevant climate hazards, scenarios and assessment methods are covered.
Pricing on request. Talk to us about your requirements and use cases.
Get in touch