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DeepSpace-AI

The Technology

DeepSpace-AI by Synthetik Applied Technologies is a software platform leveraging satellite imagery and related geospatial data sources with cutting-edge machine learning capabilities for a wide range of environmental monitoring and forecasting tasks, with wide-ranging applications for government and industry.

Applications

  •  Forecasting and monitoring of environmental phenomena such as harmful algal blooms
  • Quantifying and predicting trends in environmental indices such as presence of vegetation and surface water
  • Measuring impacts to the built environment from natural or human-made disasters
Software screenshot showing weather patterns

Benefits

  • Temporally and spatially aligned ingestion of satellite and in-situ data sources for environmental characterization 
  • Characterization and inventory of environmental and anthropogenic assets
  • Automated processing of data to identify key environmental behaviors and trends
  • Built-in deep learning frameworks for tasks such as time-series prediction and object detection, customizable to specific user needs
 

Resources

Company Contact

This technology is commercially available for purchase. For additional information please contact Josh Hatfield at hatfield@synthetik-technologies.com. Note: Any reference obtained from this website to a specific company, product, process, or service does not constitute or imply an endorsement by NOAA.

Federal Procurement – Sole Source Information

Through the SBIR/STTR Congressional Authority and Policy Directive, companies are eligible for Phase III sole-source contracts to support work that derives from, extends, or completes work funded with SBIR Phase I or Phase II awards. Technologies in the Marketplace that include this statement are eligible for Phase III awards from any federal agency. For more information about Phase III, see this website and reach out to noaa.sbir@noaa.gov with questions. Find a full list of available SBIR/STTR technologies, access the Award Database on SBIR.gov.