Intelligent Edge AI technology with real-time data processing and high security provides a safe and efficient digital experience anytime, anywhere.
Mission
We are building a next-generation smart environment by developing a high-performance Edge AI device that integrates security, safety, and convenience features required in everyday life and industrial settings.
Core business areas
Intelligent Security Surveillance System
Real-time object recognition device
Smart Home/Building IoT Solutions
Industrial predictive maintenance sensors
Core competencies
Lightweight AI modeling, low-power NPU optimization, real-time video analysis, and
edge computing security.
On-Device AI/Edge AI Market Trends
Edge AI market growth
Edge AI Market Outlook (2023-2028)
Global Market Size: $8.9 Billion by 2025
The explosive growth of the AI chip and edge device ecosystem.
Key Trends
Micro AI proliferation
Ultra-lightweight models - High-efficiency AI models ranging in size from 50KB to 500KB.
On-device inference - real-time processing on the device without the cloud.
Enhanced privacy - secure processing without external data transmission
Low-latency response - real-time decision-making in milliseconds
Application diffusion
Diversification of application areas
Security cameras
Wearable devices
Smart appliances
Industrial Edge Gateway
Skill Points
Model optimization (quantization and pruning)
NPU/TPU utilization
Power budget optimization
Knowledge Distillation
Security, safety, and convenience features examples
Security
Real-time face/intrusion detection and identification
Line crossing detection and approach notification
On-device masking for privacy protection
Safety
Real-time alert when approaching a danger zone
Early detection of abnormal sound, smoke, and heat
Early detection of equipment abnormalities and safe shutdown
Convenience
Voice and gesture natural language interface
Predictive Maintenance Notification Service
Local LLM-based data analysis and summarization
Global Edge AI Hardware Leader
NVIDIA Jetson
A leading platform for AI edge computing
High-performance GPU acceleration
JetPack SDK
CUDA ecosystem
Low-power inference based on Edge TPU
Google Coral
Low-power inference based on Edge TPU
Edge TPU dedicated needle
TensorFlow Lite
Low-power inference
Qualcomm
A leader in mobile AI chipsets
Mobile Integration
5G connectivity
Hexagon DSP
Intel Movidius
VPU vision processing specialization
Vision-specific VPU
OpenVINO toolkit
low power design
AXNOVA strategy
Ensure flexibility with multi-platform BSP support
Reduce Time-to-Market with Automated Model Porting
Selection of the optimal platform based on TOPS/W efficiency criteria
AXNOVA's Edge AI Device Development
Product Roadmap
Edge Vision Camera
Safety wearables (AR glasses and bands)
Local LLM Assistant Device
Differentiating factors
On Device Security (TEE)
Compliance with safety standards (IEC 61508)
OTA / Fleet Management SolutionOTA / Fleet Management Solution
Business model
B2B module/SDK supply
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Turnkey business
Provide solutions and consulting services for customer development
