Automotive Supplier AI Readiness Sprint
12-month roadmap in 3 weeks
Client Context
A Tier-2 automotive supplier with legacy ERP systems and limited digital maturity. The management team saw competitors adopting AI but had no internal expertise to evaluate feasibility.
The Challenge
The company wanted to know if AI-driven demand forecasting and quality inspection were feasible with their existing data infrastructure. They needed answers quickly — their largest customer was beginning to require AI-driven quality documentation.
Our Approach
Our 3-week sprint included data profiling across their ERP and quality management systems, identified critical data gaps, recommended a phased data lake implementation, and mapped a 12-month journey from data remediation to production AI.
Timeline: 3 weeks
The Results
- 12-month phased implementation roadmap delivered
- Critical data gaps identified with concrete remediation plan
- Data lake architecture designed for their specific ERP landscape
- Quick-win identified: quality inspection PoC feasible within 8 weeks
- Business case approved for first-phase investment
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