Engineering Edge AI

Adding AI to your system?
Understand the hardware decisions before committing to a design.

Deploying Edge AI means balancing processing performance with power, cooling, connectivity and long-term platform availability. Whether developing a new system or adding AI to an established platform, those choices affect integration effort, deployment timescales, and future upgrades.

Join Arad Navidi, Group FAE Manager at Captec, to explore the practical trade-offs behind Edge AI hardware selection. NVIDIA-certified and trained in Intel’s AI principles, Arad will draw on real-world application examples to explain what to assess, where compromises arise, and how to plan for evolving requirements.

Agenda

Session Duration: 45 minutes + Audience Q&A

• Deploying Edge AI across sectors: How different applications shape computing requirements
• Selecting the processing approach: CPU, GPU and NPU capabilities, and the performance/power trade-offs
• Engineering the complete system: Integrating inputs and connectivity with thermal, physical and environmental requirements
• Designing for the next release: Platform availability, revision control and long-term deployment
• Who should attend: Engineering, technical, product and procurement professionals involved in evaluating, specifying or selecting computing hardware for AI-enabled systems.

Presenter

Arad Navidi 
Group FAE Manager, Captec