Aurex Insights
Practical AI thinking for the lighting industry
Security, performance, strategy, and what actually matters when deploying AI in B2B product workflows.
How to Protect Your Business Data in the Age of AI
Most AI tools process your data on shared infrastructure. Here's what that means for your business, and how to choose a deployment model that keeps your proprietary information safe.
Speed, Accuracy, Cost: The Performance Tradeoffs in Every AI Engine
Every AI deployment is juggling four levers at once — accuracy, latency, cost, and retrieval effort. Here's how to understand the tradeoffs and find the right balance for your use case.
Why Your AI Product Assistant Should Come from Your Manufacturer, Not a Platform
Platform-neutral AI tools serve everyone in your category — including your competitors. Here's why manufacturer-sourced AI product intelligence is fundamentally different, and what to look for when evaluating your options.
The Real Cost of Not Knowing: A Financial Case for AI Product Intelligence
Every minute a rep spends hunting for a spec sheet, every configuration error that reaches manufacturing, every lost sale at the moment of a unanswered question — these have a measurable cost. Here's how to calculate it.
Your Reps, Distributors, and Designers Are Your Business — Who Else Has Access to Them?
When your network uses shared AI platforms to navigate your products, their queries, comparisons, and decision patterns flow to infrastructure you didn't choose. Here's why that matters and what to do about it.
How to Evaluate an AI Product Assistant for the Lighting Industry
Every AI vendor claims accuracy, speed, and ease of use. This guide gives you seven specific criteria — and the questions that surface real answers — for evaluating AI product tools in a lighting context.
Glossary: AI Terms Every Lighting Specifier Should Know
AI terminology lands differently depending on who's using it. This glossary defines the terms that come up most often in AI product intelligence conversations — with plain-language explanations and lighting industry examples.
How Distributors Are Eliminating Order Errors with AI Product Intelligence
Configuration errors, wrong part numbers, incomplete orders — these aren't random. They cluster around gaps in product knowledge at the moment a decision is made. Here's how AI product intelligence addresses each error type at its source.
AI in the Lighting Industry: What's Actually Changing in 2026
The lighting industry is receiving a steady stream of signals that AI is transforming product sales and specification. This article separates what's actually happening from what's still early — and where the practical opportunities are.
What Makes a Product Catalog Ready for AI?
AI product intelligence is only as good as the documentation behind it. Most lighting catalogs weren't built for machine reading — here's what AI-ready documentation looks like and how to get there without a complete overhaul.