Edge computing

AI on the Edge

Computing power closer to the data-source. Real-time actionable decisions, maximize accuracy, speed and privacy.

Shorten the gap

With edge computing AI algorithms run directly on hardware devices, reducing the distance between the data generation and its processing, preserving data privacy.

Get our AI on the edge brochure, find real-world insights and use cases.


Pose & detection

Our models’ speed and accuracy are optimized to match the latest state-of-the-art techniques.


We developed Norfair, our customizable lightweight Python library for real-time multi-object tracking.


Fast video processing pipelines using DeepStream in embedded devices, Cloud or desktop GPU.

IoT for different industries

IoT transforms how industries interact with their customers, data and devices. Edge computing mitigates network limitations, reduces energy consumption, increases security and improves data privacy.

Consumer electronics

Consumer electronics







Industrial & Quality Control

Industrial & Quality Control

On the edge partners

We have partnered with the best in the business to provide the finest edge computing solution possible.

Tryolabs partners with NVIDIA & BDTI

Together with BDTI, NVIDIA and Jabil, we created Maskcam, a product capable of running a real-time deep learning face mask detection model on an embedded device: real-time AI on the edge.

Helmet detection

Monitoring helmet usage in different scenarios leads to useful insights to take preventive actions, saving time and resources. Partnership with Seeed.

Tryolabs IoT Squad

We are constantly researching on how to address challenges like optimizing algorithms for lowering power consumption, using less computing and optimizing inference times for specific hardware. We also benchmark different hardware platforms to be ready to tackle state-of-the-art Ai-IoT problems.

IoT team

Tackle the most challenging
Iot problems with AI