AI Summary
What this page explains
Data acquisition framework for capturing what every quote, drawing review, sample approval, production job and customer feedback event teaches the platform.
- Best for: building proprietary industry intelligence from real work.
- Common applications: compatibility growth, installation support, benchmarks, CRM feedback and RFQ automation.
- Recommended action: capture evidence and data at every quote, sample and production stage.
Knowledge Flywheel
Capture model
Every time a protector is quoted, sampled, manufactured or shipped, ask what can be learned that improves the platform.
| Events | quoteSubmitted: industry, device, country, size, material preference, quantity, application, drawingReviewed: active area, outer dimensions, corner radius, cut-outs, tolerance risk, sampleApproved: fit outcome, material chosen, finish chosen, installation notes, productionCompleted: lead time, defect categories, packaging, QC findings, customerFeedback: installation issues, field failure, cleaning compatibility, reorder timing |
|---|---|
| Publishing rules | remove customer identity, aggregate commercial data, publish device-independent lessons, turn repeat questions into guidance |
| Data file | /data/data-acquisition-framework.json |
Internal Link Engine
Connected intelligence paths
Every Phase 4 asset feeds the same flywheel: quote data, display data, installation evidence, standards context, CRM outcome and publishable insight.