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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.
Tracking
We developed Norfair, our customizable lightweight Python library for real-time multi-object tracking.
DeepStream
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
Automotive
Healthcare
Telecom
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.
Tackle the most challenging
Iot problems with AI
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