MISSION & VISION OF
GENGENAI
We tackle the data deficiency problem in
the AI industry by leveraging
our domain-specific generative
AIs to the fullest extent.
MISSION & VISION OF
GENGENAI
We tackle the data deficiency problem in
the AI industry by leveraging
our domain-specific generative
AIs to the fullest extent.
Why Data Matters?
"To achieve cutting-edge AI
performance in real-world
applications, such as autonomous
driving, the collection of vast
amounts of data is imperative."
To cope with various situations,
AI must be trained with an almost
infinite array of environments,
situations, and objects.
Generative AI
for Synthetic Data
Traditional AI Dev. Cycle
Real data collected entirely by
human resources
GenAI-based AI Dev. Cycle
Automatically generated domain-specific
synthetic data using our technology
Target Domain
· GENGEN AI delivers high-quality data and annotation generation solutions tailored for Vision AI.
· We go beyond traditional data collection by solving data scarcity through synthetic data generation, enabling AI models to learn from scenarios that are rare, difficult, or costly to capture in the real world.
Home Electronics
Autonomous Driving
Defense
Surveillance
Products
GenGenData TM
Multi-Sensor Sim2Real Technology
· GenGenAI enables high-fidelity Sim2Real data generation across multiple sensors.
· Our platform supports both RGB simulators and IR simulators, allowing seamless development and validation of vision AI models in realistic environments.
Multi-Sensor Video Generation
Multi-Sensor Capability
EO/IR
EO/LiDAR
EO/SAR
Satellite/Radar
GenGenVisionTM
EO/IR
Vehicle Detection
EO/SAR
Ship Detection
EO/IR
Drone Detection
| Training Data | F-measure |
|---|---|
| Generated Only | 99.8 |
| Training Data | mAP50 |
|---|---|
| Real Only | 61.5 |
| Generated Only | 68.5 |
| Training Data | mAP50 |
|---|---|
| Real Only | 60.0 |
| Generated Only | 67.2 |
GenGenStudio - On-Premise Sim2Real Platform
Coming 2026
GenGenStudio is an on-premise platform for AI data generation, combining Sim2Real conversion and generative world modeling to produce scalable training data.