Overview
Not all AI needs the cloud. In many cases, factories, hospitals, vehicles, on-site devices, AI needs to run directly at the edge.
We build AI systems that operate locally on devices, enabling real-time decisions without needing internet or server calls. Whether it’s detecting anomalies on a machine, classifying footage on a security camera, or running personalized models on a phone. Edge AI delivers low-latency, high-efficiency intelligence where traditional cloud solutions fall short.
Perfect for businesses with privacy concerns, real-time requirements, or offline operations.
How it works
1. Define the Use Case
We begin by identifying where edge deployment makes sense, whether for speed, security, or operational efficiency.
2. Choose the Right Hardware
From NVIDIA Jetson to Raspberry Pi to custom microcontrollers, we help you select the optimal hardware for performance and cost.
3. Build Lightweight Models
We design and train models that are optimized for edge constraints, small in size, low on power, high on accuracy.
4. Deploy and Integrate
Once ready, the model is embedded directly into your device or local system with fallback logic, firmware compatibility, and update pathways.
5. Monitor and Update
We provide post-deployment tools to monitor usage, track performance, and push over-the-air updates or retrain as needed.