EagleEye
Military-certified & first to the ROK Army AI Center
proves operational readiness and trust for defense AI.
End-to-end synthetic data + LLMOps/MLOps pipeline
automates generation, labeling, validation, and deployment.
Prompt-based image generation with object/background control
rapidly scales high-quality, task-specific datasets.
Fully in-house stack for rapid updates & mission tailoring
shortens dev/validation time and avoids vendor lock-in.
EagleEye is a a synthetic data generation & management platform for AI training—spanning image generation, LLMOps, and MLOps—that passed official “military suitability” tests and became the first AI product delivered to the ROK Army AI Center, accelerating secure Sensor-to-Shooter model development and deployment.
Products & Services
KWM-Ocelot
funzin
Solution Overview
KWM-Ocelot (AI Electromagnetic Spectrum Reconnaissance System) is a self-developed solution that measures field strength and clearness of 5G/4G base station signals and automatically analyzes abnormal waveforms based on time-series data.
Main Features
Real-time wideband frequency scanning using an RF detector mounted on unmanned complex systems
AI-based signal characteristics and transmitter location analysis
Real-time transmission and visualization of analysis data to ground control stations (GCS) via data link
Identification of locations such as enemy drone and equipment operation areas, and command posts
Effective tracking and jamming of enemy communications
Key Advantages
Automated signal classification and pattern learning based on AI
Real-time visualization of battlefield electromagnetic spectrum distribution
Effective signal detection, analysis, and tracking in various military environments
Fully in-house developed, enabling rapid technological application and operational optimization
Applied Cases
Winner of the Grand Prize (Army Chief of Staff Award) at the 2025 Army Artificial Intelligence Idea Contest
Real-time reconnaissance of battlefield electromagnetic environments and enemy communication tracking in military operations
KWM-Ocelot (AI Electromagnetic Spectrum Reconnaissance System) is a self-developed solution that measures field strength and clearness of 5G/4G base station signals and automatically analyzes abnormal waveforms based on time-series data.
Main Features
Real-time wideband frequency scanning using an RF detector mounted on unmanned complex systems
AI-based signal characteristics and transmitter location analysis
Real-time transmission and visualization of analysis data to ground control stations (GCS) via data link
Identification of locations such as enemy drone and equipment operation areas, and command posts
Effective tracking and jamming of enemy communications
Key Advantages
Automated signal classification and pattern learning based on AI
Real-time visualization of battlefield electromagnetic spectrum distribution
Effective signal detection, analysis, and tracking in various military environments
Fully in-house developed, enabling rapid technological application and operational optimization
Applied Cases
Winner of the Grand Prize (Army Chief of Staff Award) at the 2025 Army Artificial Intelligence Idea Contest
Real-time reconnaissance of battlefield electromagnetic environments and enemy communication tracking in military operations
KWM : Kill Web Matching
funzin
Solution Overview
The AI-Based Command Decision Support System, "KWM," identifies battlefield targets and recommends optimal weapon system combinations. It supports end-to-end "Sensor-to-Shooter" execution for rapid, accurate, and efficient engagement and command decision-making.
Main Features
Identifies targets on the battlefield using integrated sensors and data
Recommends the most effective attack strategies for both reconnaissance and attack missions
Provides command decision support through real-time analysis and visualization
Suggests and allocates optimal target formations and strike assets
Supports on-site command and control with a user-friendly interface
Key Advantages
Enables quick, accurate, and efficient engagement of enemy targets
Automated recommendation of attack strategies and allocation of strike resources
Real-time synchronization between reconnaissance and attack kill webs
Direct connection from detection to strike (Sensor-to-Shooter capability)
Increases operational efficiency and decision-making accuracy in complex battlefield environments
Applied Cases
Successfully piloted in the Army Tiger Boost Project in 2024
Used for command decision-making and efficient allocation of attack resources in live military scenarios
The AI-Based Command Decision Support System, "KWM," identifies battlefield targets and recommends optimal weapon system combinations. It supports end-to-end "Sensor-to-Shooter" execution for rapid, accurate, and efficient engagement and command decision-making.
Main Features
Identifies targets on the battlefield using integrated sensors and data
Recommends the most effective attack strategies for both reconnaissance and attack missions
Provides command decision support through real-time analysis and visualization
Suggests and allocates optimal target formations and strike assets
Supports on-site command and control with a user-friendly interface
Key Advantages
Enables quick, accurate, and efficient engagement of enemy targets
Automated recommendation of attack strategies and allocation of strike resources
Real-time synchronization between reconnaissance and attack kill webs
Direct connection from detection to strike (Sensor-to-Shooter capability)
Increases operational efficiency and decision-making accuracy in complex battlefield environments
Applied Cases
Successfully piloted in the Army Tiger Boost Project in 2024
Used for command decision-making and efficient allocation of attack resources in live military scenarios
Description
Solution Overview
EagleEye is a a synthetic data generation & management platform for AI training that integrates image generation, LLMOps, and MLOps. It automates high‑quality dataset generation, labeling, and model validation—and has been certified “military suitable” and delivered first to the ROK Army AI Center.
Main Features
Image generation with text/image prompts; object/background customization
LLMOps: prompt understanding + image–text labeling workflow
MLOps: CV model training/validation, dataset versioning, experiment tracking
End‑to‑end pipeline from data preprocessing to model deployment
Data augmentation and management for scalable, repeatable training
Key Advantages
Certified “military suitable”; meets defense operational requirements
First AI solution supplied to the ROK Army AI Center, proving reliability
One‑stop synthetic data + model ops cuts development/validation time
Fully in‑house stack enables rapid updates and mission‑tailored customization
2025: First AI product delivered to the ROK Army AI Center for defense AI projects
Used to generate and manage high-quality synthetic imagery for military AI model training and validation
EagleEye is a a synthetic data generation & management platform for AI training that integrates image generation, LLMOps, and MLOps. It automates high‑quality dataset generation, labeling, and model validation—and has been certified “military suitable” and delivered first to the ROK Army AI Center.
Main Features
Image generation with text/image prompts; object/background customization
LLMOps: prompt understanding + image–text labeling workflow
MLOps: CV model training/validation, dataset versioning, experiment tracking
End‑to‑end pipeline from data preprocessing to model deployment
Data augmentation and management for scalable, repeatable training
Key Advantages
Certified “military suitable”; meets defense operational requirements
First AI solution supplied to the ROK Army AI Center, proving reliability
One‑stop synthetic data + model ops cuts development/validation time
Fully in‑house stack enables rapid updates and mission‑tailored customization
2025: First AI product delivered to the ROK Army AI Center for defense AI projects
Used to generate and manage high-quality synthetic imagery for military AI model training and validation
