About Edge AI Stack

Edge AI Stack is a vendor-neutral, engineering-first resource for teams building and operating AI systems outside the cloud. The focus is on the constraints that actually shape decisions in the field: hardware budget, power envelopes, thermal limits, storage endurance, network reliability, and the cost of keeping a system running for years — not just getting it through a demo.

Coverage spans AI accelerator hardware, inference runtimes, edge networking, storage selection, power design, and fleet management. Articles are written for engineers who need to make purchasing and architecture decisions with incomplete information and real deadlines.

Mission

To provide practical, reproducible guidance for edge AI infrastructure — grounded in specs, benchmarks, and deployment experience rather than marketing narratives. Hardware and software are evaluated on how they perform under the conditions that matter: sustained load, thermal stress, long write cycles, and constrained power budgets.

Editorial Principles

• Clarity over completeness: every article focuses on the decision at hand, not an exhaustive survey of every option.
• Repeatability: configurations and test conditions are stated explicitly so results can be verified or reproduced.
• Real constraints first: power, cost, thermals, and maintainability are treated as first-class requirements, not afterthoughts.
• Kept current: articles are revised when hardware generations, firmware updates, or price shifts make earlier guidance inaccurate.