Why is this course a must for manufacturers?
For manufacturing, AI isn't about "good enough to use"—it's about "can't afford to be wrong"
 
 
 
Zero-error pressure: scheduling mistakes, quality-control misjudgments, and missed deadlines—once AI gets it wrong, it means cost and customer complaints.
 
 
Black-box risk: why did the AI make that judgment? If it can't be traced, you can't answer to your customers or your own team.
 
 
The tool-failure cycle: when ERP / CRM / BI implementations fail, the root issue isn't the tool but a lack of process design and acceptance-testing capability.
 
 
 
 
After this course, you'll come away with
 
✅ AI that's controllable (not a black box)
 
✅ Traceable processes (every step has a log)
 
✅ Verifiable decisions (someone is accountable)
 

Course Positioning
Course Objectives
 
This is a hands-on course designed specifically for non-technical business owners, managers, and administrative staff. We put AX Academy's enterprise-transformation methodology into practice with the Open WebUI (OpenGenie) tool. We don't just teach you AI chat—we teach you how to build a company-exclusive AI system where "data never leaves home," with access control and knowledge retention built in.
 
 
 
Why is this course a must for beginners and managers alike?
 
 
 
 
Zero security risk: learn the logic of on-premises private deployment so confidential documents like contracts and financial reports never flow to third-party servers.
 
 
 
 
Zero communication barrier: the interface is as friendly as ChatGPT, so your whole company can get up to speed painlessly.
 
 
 
 
24h post-course teaching assistant: after the course, you get an AI teaching assistant based on the course content to answer your hands-on questions anytime.
 
 
 
 
 
Course Structure
 
Five Core Tasks
 
1. AI Literacy and Manufacturing Risk Principles (AX L0–L1)
 
 
 
 
A guide to avoiding pitfalls in enterprise AI adoption:Why can't manufacturers use ChatGPT directly for decision-making?
 
 
 
 
Building a zero-error mindset:Understand the risks of AI hallucinations in quality control, scheduling, and customer service
 
 
 
 
AI collaboration fundamentals:Establish enterprise AI usage guidelines and risk awareness
 
 
 
 
 
2. Process-Design Thinking × Getting Started with n8n (L1–L2)
 
 
 
 
Visual process design:Use n8n to build enterprise processes (Trigger / Logic / Output)
 
 
 
 
Low-code in practice:Complete automation-process design without writing code
 
 
 
 
Process standardization:Turn experience into a "repeatable process"
 
 
 
 
 
3. Automating Sales Data and Reports
 
 
 
 
Data integration:Read from Excel / Google Sheets
 
 
 
 
AI auto-summary:Generate sales analysis and market insights
 
 
 
 
Automated report delivery:Build automated workflows for weekly / monthly reports
 
 
 
 
 
4. Hands-On Sales-Process Automation (Core)
 
1️⃣ Automated reporting flowData → AI analysis → automatic output
 
2️⃣ Customer-service intent classificationCustomer message → AI interpretation → automatic classification
 
3️⃣ Performance anomaly alertsData anomaly → AI judgment → real-time notification
 
 
 
5. Controllable AI Architecture (Harness) and Governance Mechanisms
 
 
 
 
Logging mechanism:Every AI decision step is traceable
 
 
 
 
Human-in-the-loop：Introduce human confirmation for key decisions
 
 
 
 
Decision-accountability design:AI assists, but accountability remains clear
 
 
 
 
 
Course Highlights
 
✅ AI design built specifically for manufacturing (not a generic course)
✅ A controllable AI architecture (rare in the industry)
✅ Take home three hands-on automation workflows
✅ Visual operation (zero coding barrier)
✅ The AX maturity model (with a clear upgrade path)
 
 
 
Learning Outcomes
 
 
 
 
Master process-automation skills:Design n8n automation workflows independently
 
 
 
 
Build AI application capabilities:Let AI assist with report analysis and decision support
 
 
 
 
Build a controllable AI system:Equipped with logging, acceptance-testing, and governance capabilities
 
 
 
 
Take home an enterprise adoption blueprint:An AI adoption path from L0 → L2
 
 
 
 
 
Who Should Attend
 
 
 
 
Manufacturing managers / owners:Want to adopt AI but don't want to hit pitfalls
 
 
 
 
Sales / marketing staff:Need automated reports and customer analysis
 
 
 
 
Information / IT departments:Responsible for enterprise systems and process integration
 
 
 
 
Administration / PM:Want to boost efficiency and reduce manual work