Expanding the space infrastructure through on-orbit data processing services
Check out our Equity Crowdfunding Campaign
Instead of raising our first round of financing the traditional way, through VC's, we decided to engage more directly with the space community by raising funds through an equity-based crowdfunding campaign on Spaced Ventures. We see our early investors as a huge asset because they provide such a strong network and positive conversation. Join the Exo-Space team by investing today!
Click here to become an
Shared Image processing platform in space
The FeatherEdge platform runs artificial intelligence and machine learning (AI/ML) models on satellite imagery as it's collected, all on-orbit. Processed data can be delivered to users within an hour of image capture.
GET REAL-TIME INSIGHT ON SATELLITE IMAGERY
ONLY PAY FOR THE RELEVANT INFORMATION
No need to go through hundreds of images to find the information you're looking for. Tell us the areas you want imaged and the insight you need from those images and we'll simply send you the relevant information.
TIME UNTIL LAUNCH
Users can choose to upload their own AI/ML models to the platform or have us develop a custom application for you. Models are capable of being configured and updated in orbit to meet the changing mission needs of any user.
Exo-Space's FeatherEdge Platform provides real-time insight on Earth Observation data
Each day satellites send over 1 million raw photos to Earth. Images are being created faster than they can be sent to the ground and in the next 3 years satellite cameras will be producing images at a rate of 1 gigabyte per second. That's the equivalent of 400 HD photos every second. Satellites waste approximately 30% of bandwidth on photos that are unusable (i.e. contain clouds, out of focus etc.)
Earth Observation systems are unable to downlink data to centralized cloud services continuously, but they still have a continuous stream of data which requires large amounts of machine learning/compute resources.
Most off-grid worksites have limited bandwidth and unreliable network connections and some data (i.e. for natural disaster response) is only useful if it's processed in real-time.