AI Deep Dive for Manufacturing: A Plan That Fits Your Shop
For manufacturers tired of generic AI advice. A 2-3 day teardown of your real business: website, software, processes, and what AI says about you—with fixes shipped along the way.
You hear about AI helping factories and job shops, but most advice feels written for software companies. You need someone to look at your actual production flow, your order pipeline, and your team’s daily work, not just throw a chatbot on your site.
For a manufacturer, an AI deep dive starts where the work happens. It examines your quoting process—how a customer’s RFQ moves from email to estimate. It looks at your production scheduling, your inventory reorder triggers, and how your team logs quality checks. The goal is to find repetitive tasks that AI can handle: turning inspection sheets into digital records, auto-filling customer status updates, or suggesting better job sequences based on machine availability. No pilot projects that never ship. Every recommendation ties back to your shop floor.
A manufacturer is different because the output is physical. Machines have downtime, safety rules are real, and a bad AI suggestion can stop a line. The deep dive respects those constraints. It does not try to replace your ERP overnight or pretend a chatbot can run a CNC. Instead, it finds small, safe wins that fit around your existing equipment and your crew’s expertise.
This deep dive costs $1,500 flat. It runs 2-3 days and includes a written plan plus some fixes implemented during the dive. If your operation spans multiple locations or relies on a heavily customized ERP, the scope might stretch a little, but the base price covers a single-site manufacturer with typical software. No hourly billing, no surprise invoices.
It starts with a short phone call to understand your pain points. Then Scott Gerke reviews your website, your internal tools, and how AI platforms describe your business online. He talks to your team, watches your order-to-ship flow, and tests small automations on your own data. By day two or three, you get a plain-language report that ranks AI opportunities by effort and impact, and you already see one or two of those working.
When it’s done, you have a clear, prioritized list of AI moves that make sense for a manufacturer. A few are already live. You know exactly what to tackle next, and you have a partner you can call when you’re ready.