Innovative Intelligent Systems for Space Technology & Space Exploration

Predicting Loss of Communication

The majority of space systems are subject to real-time signal loss with little or no advanced warning. Our technology learns the comm system environment and predicts loss of signal, providing advanced warning to drive key mission decisions. Infuse this technology in your ground or onboard system to mitigate costly failures.

Provide advanced warning to preserve mission objectives
Real-time loss of signal prediction and mitigation

Forecasting Solar Activity & Space Weather

We advance space weather forecasting at its origin: the Sun. As the Sun becomes more active and exceeds traditional model predictions in Solar Cycle 25, our technology seeks to outperform all predictive models, giving advanced warning of highly disruptive solar events with downstream effects on Earth and in the near-Earth environment of Earth’s magnetosphere. Supplement your suite of console operations tools with solar activity forecasting to preserve and protect your space assets.

Provide advanced warning of solar activity to protect space assets
Power space weather software tools with AI

Enhancing Space Operations

Embedding AI/ML within your console tools will minimize the subjective nature of calls made by your flight control staff in your operations center. Embedding AI and ML within your onboard systems will provide your spacecraft subsystems with an enhanced level of autonomy, removing a level of required commanding from flight controllers on the ground.

Minimize the element of human subjectivity
Power onboard systems and console tools with AI

Space Data Analytics

We implement AI/ML is space systems to enhance the processing and integrity of your space data, onboard your spacecraft or with in your ground processing pipeline. Extract the preliminary science results from your image data to rapidly drive the next sequence of science observations.

Maximize space system performance
Intelligent analysis of spacecraft systems and instrument science data