Vision-native edge AI
Fully local edge AI autonomy with eye³ aiVISIONOS embedded inside.
Why it matters
Most AI cameras only classify pixels. They rely on the cloud, suffer latency, and fail when the factory floor or warehouse changes.
The edge-vision market already exceeds $25 billion and is growing ~20% per year. Customers need privacy, resilience, and adaptation.
eye³ pairs a 20 TOPS Edge-AI SoC with an embedded 7B LLM. The camera reasons, explains, and improves without the cloud.
Edge performance
Latency per inference on RK3588 + Renesas RZ/V2N
AMR uptime in mixed-traffic pilots
Battery-life gains from on-device reasoning
False-positive reduction for low-light ADAS
Deployment plays
Navigation, visual odometry, obstacle avoidance with <1 cm path accuracy.
See AMR stack
Edge defect detection, OCR, and adaptive line tuning for 24/7 production.
Inspection playbook
Driver-assist vision modules, in-cabin analytics, and human intent sensing.
Explore ADASGenerative hardware
Wearable or vehicle-mounted cameras that see, reason, and explain. Perfect for co-bots, industrial safety, and assistive tech.
View reference designArchitecture
| Pillar | Description |
|---|---|
| Empathic Intelligence | Sees beyond pixels — understands human context and intent. |
| Self-learning engine | Adapts autonomously from real-world feedback. |
| Generative vision | Reconstructs, enhances, and imagines what standard sensors miss. |
| Edge autonomy | 100% local — no cloud, no latency, full privacy. |
Proof points
35% throughput gain and 30% longer battery life in a 60-robot deployment.
92% fewer false positives in low-light testing with embedded reasoning.
95% motion-tracking accuracy for elite performance data capture.
Partner with us
OEMs, integrators, and research labs use our modules and SDKs to accelerate autonomy programs. Co-develop reference hardware, safety cases, and fleet telemetry.
Get in touch
Discuss your robotics project with our Edge AI engineers. We’ll recommend the right SoC, optics, and SDK profile for your application.