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AI IntegrationManufacturing·MENA·22 weeks (phase 1)
Embedding AI copilots across the operations stack of a mid-market manufacturer
Delivered a portfolio of AI copilots — for procurement, quality and maintenance — connected to ERP, MES and CMMS, reducing unplanned downtime 29% in the first year.
Client · Falcon Industrials
Impact
Results at a glance
−29%
Unplanned downtime
−41%
Procurement cycle
−18%
Quality defect rate
7 months
Payback period
The challenge
- 1Critical knowledge lived in PDFs, tribal knowledge and spreadsheets that no one indexed.
- 2Maintenance planners reacted to failures instead of predicting them.
- 3Procurement negotiated in the dark without a comparable view of supplier history.
- 4Quality inspectors used inconsistent checklists across shifts.
Our approach
- 1Ran an AI readiness assessment across data, people and processes.
- 2Prioritized use cases by value × feasibility and shipped the top three first.
- 3Set up a governance board — data, security, ops — before any model went live.
What we built
- 1Retrieval-augmented copilots grounded in ERP, MES, CMMS and document repositories.
- 2Predictive maintenance model on 24 months of sensor and work-order data.
- 3Supplier benchmarking dashboard with negotiation prompts for procurement.
- 4Vision-assisted quality checks on the highest-risk lines.
- 5Governance layer: prompt logging, PII redaction, human-in-the-loop review.
Results delivered
- 29% reduction in unplanned downtime versus the trailing 12-month baseline.
- 41% faster procurement cycle from RFQ to award.
- 18% drop in quality defect rate on instrumented lines.
- Payback achieved in 7 months — well ahead of the 14-month plan.
- Standing internal AI council now shipping two new use cases per quarter.
"AI stopped being a slide and started being a scheduled improvement in our operating results."
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