Astra Mimic
Synthetic Satellite Data for Next-Gen AI
We generate realistic, physics-based synthetic satellite data to train AI for the unobservable.
The Insight Gap
We can see the Earth. But we can’t understand it.
Data Abundance
Thousands of satellites, like the Copernicus constellation, orbit Earth daily, generating terabytes of optical and radar data. We have an unprecedented ability to see our planet.
Insight Scarcity
But seeing is not understanding. Without labeled examples of critical events (floods, landslides, soil stress) this data is just noise to an AI. The bottleneck isn't the pixels; it's the intelligence.
The Challenge
Why Current AI Models Fail
Rare Events
Critical disasters are rare by definition. They appear infrequently in historical datasets, making it impossible to train robust AI models using only real-world data.
Prohibitive Costs
Acquiring and manually labeling high-quality disaster imagery is incredibly expensive, slow, and prone to human error.
Reactive Response
Because models are trained on "normal" conditions, they fail exactly when needed most: during the anomaly. We act only after the damage is done.
The Solution
The Astra Mimic Solution
We generate realistic, physics-based synthetic satellite data to train AI for the unobservable.
Multi-Sensor
Multi-Sensor Simulation Platform
Optical Imagery
High-resolution RGB simulation for visual analysis and land use classification.
Thermal Sensors
Heat signature simulation for wildfire detection and industrial stress monitoring.
SAR Radar
Synthetic Aperture Radar to "see" through clouds and night, ensuring 24/7 reliability.
Our Edge
Physics-Based Intelligence
Unlike generic Generative AI, Astra Mimic is grounded in reality.
Physics Integration
We incorporate laws of electromagnetism and material reflectance into every pixel.
Reduced Domain Gap
Our data mimics the exact sensor noise and physical properties of real satellites.
Proven Impact
Models trained on our data show a +15–25% increase in accuracy.
Scenario Generation
Create thousands of "What-If" disaster scenarios that have never happened, yet.
Business Model
Built to Scale
Vertical Datasets
Off-the-shelf, pre-generated datasets for common use cases like flood risk assessment and crop monitoring.
On-Demand API
Scalable API access allowing clients to generate custom synthetic scenarios on the fly for specific training needs.
Recurring Revenue
High-margin SaaS model with annual subscriptions for continuous access to our simulation engine.
Market Opportunity
The geospatial synthetic data market is valued at $1.02B today and is projected to grow at >30% CAGR, driven by demand in insurance, agritech, and public sectors.
Featured Use Case
Solar Intelligence Engine
Eliminating information asymmetry in global energy markets by detecting the 30% of solar capacity invisible to traditional top-down registries.
The Blind Spot
30% of actual installed solar capacity (Commercial & Industrial) is missing from official registries, causing systematic errors in intraday price forecasting for energy markets.
Visual Truth
Using synthetic data-trained models, we scan Copernicus imagery every 2-4 months to identify "ghost" plants and extract their true physical geometry (Tilt & Azimuth).
The Alpha Signal
Transforming this physical inventory into predictive trading signals to anticipate market movements, optimize BESS cycles, and accurately price Power Purchase Agreements.
Our Mission
“The limit is not observing the Earth, but understanding it in time. We transform data into prediction, and prediction into resilience.”
— Astra Mimic
Anticipate the Future
With Astra Mimic, we don’t just react to emergencies.
We predict them.