Applied AI in Vallès industry: a use case to recover operating hours
9 August 2026 · 7 min
Applied AI is not a generic chatbot
When an industrial SME asks for AI, it often gets a spectacular demo disconnected from day-to-day work. Real value appears when AI answers operating questions with internal data and correct permissions.
Typical use case: inventory and purchasing queries
Starting point:
- Operations takes several minutes to answer stock questions.
- Purchasing manually checks availability and lead times.
- Sales depends on others to confirm an order.
Goal:
- Answer frequent operating questions in seconds.
- Reduce cross-department interruptions.
- Keep an audit trail of who asked and what they got.
Minimum viable design
- Connect a reliable source (ERP or inventory DB).
- Normalise key fields (SKU, warehouse, status, date).
- Define role-based permissions.
- Enable a natural-language query interface.
- Log queries for continuous improvement.
What to measure
- Average response time per query.
- Queries resolved without escalation.
- Hours recovered in ops / purchasing / sales.
- Errors from stale data.
Where many projects fail
- AI with no connection to real data.
- No permission control or audit.
- No workflow to correct doubtful answers.
- No business KPI from day one.
Recommended approach for Terrassa and Vallès
Start with a high-frequency, low-risk flow. If it works, layer on financial close, international quoting or commercial analytics.
At D4TA this first step is often validated with Oracle.