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Industrial AI Deployment & Integration

A topic hub for operators evaluating how to deploy industrial AI into live facilities, including camera compatibility, vendor selection, line integration, infrastructure fit, and rollout planning.

Cluster Overview

Camera compatibility, MES and ERP integration, deployment architecture, and evaluation guidance for production teams.

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Articles in this cluster

Technical Analysis

Camera retrofit economics: when your existing estate can carry AI, and when it can't

Hardware cost reductions of 30–50% are achievable when existing cameras qualify for AI inference, but retrofit economics depend on five technical disqualifiers that most existing camera estates fail to meet—resolution, sensor size, frame rate, optical performance, and mounting position. This post provides the estate survey methodology to determine which cameras qualify for retrofit versus partial upgrade versus full replacement before committing to a retrofit architecture.

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Technical Analysis

Edge vs cloud inference for factory vision: latency, bandwidth and data-residency math

Factory vision systems generating 38,400+ inference requests per shift face latency, bandwidth, and regulatory tradeoffs between edge and cloud inference; round-trip cloud latency can exceed rejection window timing on high-speed lines, making edge inference the architecturally correct choice despite higher compute costs. This post provides the latency math, bandwidth calculations, and data-residency framework needed to choose the right architecture for your line speed and data jurisdiction.

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