Space generates some of the most demanding data in existence: high volume, high velocity, multi source and only meaningful when correlated across time and orbit. Black Forest organises it as a living network of relationships rather than isolated records, so operators and analysts can connect the dots at mission tempo.
Space domain awareness
Custody of every object, in near real time
Identify, track and maintain custody of space objects at scale across a growing resident space object population.
Automate data fusion, calibration and data quality filtering, then associate and correlate objects to detect and reconstruct manoeuvres in minutes.
Multi sensor fusion for a 360 degree orbital picture, with AI and machine learning anomaly detection, conjunction analysis and pattern based threat detection.
SDA depends on relationships, interactions and evolving networks rather than isolated data points, which is exactly what a time aware knowledge graph is built for.
Earth observation
Time series knowledge search across sources
Fuse optical earth observation, synthetic aperture radar and radio frequency data into one queryable picture, expandable to any additional source.
Combine, correlate and verify across providers, so a detection in one source can be confirmed against another over the same place and time.
Temporal, relational and spatial analysis in a single engine, feeding predictive analytics, machine learning and generative AI with connected context.
Climate and environment
Multi source event correlation over time
Ingests the formats this domain actually uses, including GeoTIFF, KMZ, GRIB2, NetCDF, JSON and GeoJSON.
Co-locates discrete data products in storage, so every weather layer and data source can be queried together rather than one at a time.
Supports environmental applications from crop and land monitoring to wildfire prediction, correlating satellite data with ground sensors, weather feeds and historical records.