Our Services
Gradion EdgeAI supports Edge AI projects across the entire product lifecycle -- from initial feasibility assessment through working prototype to production-ready field deployment.
Edge AI Consulting and Feasibility Assessment
The Problem
Companies evaluating Edge AI face high uncertainty. Which hardware is the right fit? Can the required performance actually be achieved on an embedded device? What does the shift from cloud to edge mean for the existing architecture? Without well-founded answers, organizations risk months of development effort in the wrong direction.
The Approach
- Hardware evaluation and platform recommendation (NVIDIA Jetson, industrial carrier boards)
- Model benchmarking on the target hardware with real-world data
- Architecture recommendation for edge integration
- Risk assessment and resource estimation
Result
A concrete decision basis with go/no-go recommendation and implementation roadmap. Stakeholders know exactly what is feasible, what it costs, and which path is recommended -- before investing in full-scale development.
Prototype Development
The Problem
Between proof-of-concept and production-ready system lies a significant gap. A model that works in the lab may lack the performance needed on the target hardware. Integration with existing systems remains unresolved. The step from development kit to field device is larger than expected.
The Approach
- Development directly on the target hardware -- no prototype that needs to be rebuilt later
- Model optimization with TensorRT and Deepstream for maximum on-device performance
- Integration with existing systems and data infrastructure
- Performance validation under realistic field conditions
Result
A working prototype on production hardware with measured performance. Not PowerPoint slides, but a running system that proves feasibility under field conditions -- and serves as the technical foundation for production.
Production Support and Dedicated Team
The Problem
From a validated prototype to field deployment with hundreds of devices is a long road. Yocto BSP customization, security hardening, OTA update infrastructure, fleet management -- the last 80% of the journey is the most demanding. This is precisely where most Edge AI projects fail.
The Approach
- Embedded engineering team that scales with the product
- Yocto Linux for tailored, production-ready distributions
- OTA update infrastructure for secure firmware and model updates in the field
- Fleet management and monitoring for ongoing operations
Result
A production-ready Edge AI system that runs reliably on hundreds of devices in the field. Secure, maintainable, and scalable -- with a team that supports the product from prototype through ongoing operations.
Learn more about the collaboration models -- from feasibility assessment to dedicated engineering team.
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