Synthetic Data-Trained AI Image Analytics
We develop computer vision AI systems capable of automatically extracting custom insights from raw satellite, aerial, or drone imagery, even in extremely data-scarce environments. By leveraging AI, we reveal what was previously unseen.
Sectors involved in Earth Observation (aerospace, defense, agriculture, etc.) collect vast amounts of data daily. Manual analysis is futile, and automation requires well-labeled data. Continuous sensor improvements and the ever-evolving nature of target objects create numerous use cases where training data for AI automation simply doesn't exist.
When vast data exists without automated information extraction, manual processing consumes enormous resources and becomes unsustainable.
You cannot train neural networks to detect rare objects or phenomena without sufficient, well-labeled footage.
Because information remains hidden in unprocessed imagery, data assets are lost, and clients miss out on strategic advantages.
Training a neural network requires high-quality data. In most cases, this is unavailable, or slow and expensive to collect. Our synthetic data generation technology bridges this gap by creating perfect training data. Although data-related tasks typically make up 70% of AI projects, we don't stop there. We select the appropriate neural networks, execute and optimize training, and deliver high-performing AI models.
We develop AI image analytics even when the client can provide only a few sample images, preparing systems for never-before-seen events (e.g., camouflaged vehicles, disaster scenarios).
Our technology operates in hyperspectral space, making information invisible to the human eye visible through sensor fusion.
Satellites are capable of data analysis from the moment they enter orbit; there's no need to wait years for data collection.
AI analytics can be developed for sensors that don't yet exist (e.g., simulating satellite images with resolutions better than 30cm/px).
For Drone, Aerial, or Satellite Imagery
Identifying vehicles and infrastructure elements under any terrain conditions.
Sorting and classifying detected objects.
Tracking the movement of objects, vehicles, and terrain features.
Detecting missing objects or unusual events.
Customizing large, open-source models using synthetic data.
Image Enhancement & Environmental Correction
Super-resolution and denoising (e.g., 10m/px → 2m/px).
Correcting dead pixels, striping, and geometric distortions.
Software removal of haze, smog, and thin clouds.
Precise detection of clouds and shadows.
Non-Aerial Models
Quality control, missing object detection, anomaly detection.
Inventory tracking, monitoring incoming and outgoing goods.
We start with a free consultation where the client outlines the problem.
Together with the client's engineers and experts, we dive deep into mapping out the requirements.
We always propose executing a Proof of Concept (POC) project.
A POC saves immense time and cost for the full project, clarifying the best approach to the problem.
After the POC, we can precisely specify the production-ready system and calculate ROI, which executives appreciate.
At the end of the project, we can deploy (and operate) the developed analytics and suggest further iterations.
We don't just develop state-of-the-art AI systems; we help your company understand and apply them. Practical, hype-free strategy from experts on the front lines, sharing deep-tech development experience instead of PowerPoint fluff.
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