Define site needs
Confirm camera counts, resolution, frame rate, model size and latency; distinguish offline analysis from real-time inference.
AI / REFERENCE ARCHITECTURE
Edge AI & Vision Inference
Plan around models, video inputs and the realities of the deployment site.
Hardware and application reference imageryBUILD AROUND THE WORKLOAD
Work through the technical requirements
Match the edge platform
Assess accelerators, decoding, model formats and system resources rather than choosing on TOPS alone.
Connectivity & reliability
Check network, storage, power and temperature limits. Industrial suitability needs model-specific evidence.
Deployment & maintenance
Plan updates, outages, event logging and access controls; test false positives and negatives in representative conditions.
REFERENCE WORKFLOW
Define the workflow before the hardware.
- 01Workload
- 02Compute
- 03Data & links
- 04Validate & operate
This is an architecture planning approach, not a completed case study or performance commitment. Agree software, equipment and service scope per project.
What do we need next?
Applications and models, data scale, user or node counts, latency and throughput goals, existing resources, budget and site constraints. Existing measurements help narrow the shortlist.
Turn requirements into a reviewable plan
Discuss selection, bills of materials, samples and procurement on a project basis. Model availability, implementation, installation and validation scope require agreement after requirements review.
Discuss your technical requirements ↗LET’S BUILD YOUR NEXT CONFIGURATION
Discuss your requirements ↗