Edge AI Specialist
From 50% to 95% detection accuracy — in production
Gradion EdgeAI takes your Edge AI from prototype to series production. As a specialized partner for NVIDIA Jetson, Gradion EdgeAI combines deep technical expertise with the delivery capability of a 600-person organization — ISO 27001-certified.
Discuss your projectGradion
Part of Gradion Group
600+ Experts
Enterprise-wide Competence
ISO 27001
Certified Processes
5+ Years Jetson
Production Experience
Our Services
Three engagement models that take your project step by step from concept to series production.
Feasibility Analysis
2-3 WeeksRapid feasibility assessment for your Edge AI initiative. Gradion EdgeAI evaluates your current architecture, identifies on-device processing potential, and delivers a concrete recommendation with roadmap.
Learn morePrototype Sprint
6-10 WeeksA working proof-of-concept on your target hardware. Gradion EdgeAI validates performance and integration under real-world conditions — every architecture decision is made with series production in mind.
Learn moreDedicated Team
OngoingAn embedded engineering team for production development and long-term optimization. From Yocto BSP to security hardening to fleet management — Gradion EdgeAI brings your product to field deployment.
Learn moreCase Study
A Leading Traffic Monitoring System — Intelligent Traffic Analysis in Production
For the customer, Gradion EdgeAI brought a leading traffic monitoring system from prototype to series production — with on-device AI on NVIDIA Jetson, TensorRT-optimized inference, and a production-hardened architecture.
The result: hundreds of autonomous sensor units deployed in the field, detecting, tracking, and counting 11 vehicle classes in real time — in any weather, around the clock.
Read case study50% → 95%
Detection Accuracy
Hundreds
Units in the Field
<200ms
End-to-End Latency
Technology Partners
From the Field
Technical insights from our work with Edge AI, NVIDIA Jetson, and production systems.
TensorRT Is Not Enough: What We Learned Optimizing for Jetson
Why real inference optimization on NVIDIA Jetson goes far beyond model conversion — and what the entire pipeline has to do with it.
Read moreJetPack or Yocto? Why We Switch for Hundreds of Field Devices
NVIDIA JetPack is fine for the prototype. For hundreds of devices in the field, you need more — on migrating to a custom Yocto distribution.
Read moreGDPR as an Architecture Advantage: Why On-Device AI Ends the Privacy Debate
Instead of bolting on compliance after the fact, on-device processing solves the problem architecturally — making the data privacy debate moot.
Read moreReady for your Edge AI project?
Let us discuss how to bring your vision to production.
Discuss your project