Why HelioChip Software
Our edge AI software operates directly on your devices - Subscription-based licensing with built-in AI capabilities
Edge Processing Power
Ultra-low latency AI inference running directly on edge devices
Real-Time Intelligence
Instant decision-making with millisecond response times
Enhanced Security
Data processed locally reduces cloud transmission risks
Seamless IoT Integration
Connect and manage thousands of IoT devices effortlessly
Software Solutions for Every Industry
Our edge AI software operates across IoT devices in multiple industries
Smart Vision Systems
Real-time video analytics and object detection at the edge
Industrial IoT
Predictive maintenance and quality control for manufacturing
Smart Buildings
Energy optimization and automated building management
Autonomous Vehicles
Edge AI for real-time decision making in autonomous systems
Smart Metering
Real-time energy monitoring and consumption analytics
Security & Surveillance
Intelligent threat detection and automated response systems
How We Work
Our proven process for deploying HelioChip software on your IoT devices
Assessment
We analyze your IoT infrastructure and identify edge AI opportunities
Design
Custom edge AI architecture tailored to your specific requirements
Deployment
Seamless integration with your existing IoT ecosystem
Optimization
Continuous monitoring and performance enhancement
What Our Clients Say
Success stories from companies leveraging edge AI
"HelioChip's edge AI software reduced our production downtime by 85%. Real-time analytics running on our devices transformed our operations."
"Their smart building solution cut our energy costs by 40% while improving tenant comfort. Outstanding results."
"The real-time threat detection system has improved our response time by 90%. Exceptional technology and support."
Edge AI Technologies
Cutting-edge technologies powering our edge AI platform
TinyML Models
Ultra-efficient ML models optimized for resource-constrained devices
Neural Processing Units
Dedicated AI accelerators for lightning-fast inference at the edge
Federated Learning
Train models across distributed devices while preserving privacy