Case Studies/Automotive
Contact Centre AI Chat Assistant with RAG & Azure OpenAI
Fortune 100 US Automobile ManufacturerRegion: North AmericaDuration: 18 months
$15.1M
Cost Savings
30%
Processing Time Reduced
99%
Data Accuracy
40+
Systems Modernized
Case study highlightsAt a glance —
At a glance —
the essentials.
The Customer
Fortune 100 US Automobile Manufacturer
Industry: Industry: AutomotiveRegion: Region: North AmericaDuration: Duration: 18 months
banking
Business Challenge
- The client operated 40+ aging mainframe systems that were expensive to maintain, slow to adapt, and creating bottlenecks across their global supply chain and manufacturing operations.
Our Solution
- Kumaran deployed an AI-driven modernization strategy using automated code analysis, refactoring tooling, and phased migration to modern cloud-native platforms. Each system was catalogued, assessed, and migrated with zero disruption to ongoing operations.
Key Results
- $15.1M in estimated annual cost savings achieved
- 30% reduction in end-to-end processing time
- 99% improvement in data accuracy across all migrated systems
- 40+ legacy mainframe systems fully modernized
- Eliminated dependency on costly COBOL expertise
By the numbers
$15.1M
Cost Savings
30%
Processing Time Reduced
99%
Data Accuracy
40+
Systems Modernized
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Go deeper — download the PDF
The downloadable report includes the complete technical narrative beyond the highlights above:
- Platform Specifications — Hardware, OS, runtime environment, and infrastructure topology — including detailed configuration of the source and target platforms.
- Architecture Diagrams — Before-and-after system topology, data flows, integration patterns, and component interaction maps from the production deployment.
- Project Scope — Workstreams, team structure, governance model, RACI matrix, and the phased delivery plan that kept stakeholders aligned.
- Migration Methodology — Phased cutover plan, parallel-run validation harness, automated regression strategy, and rollback playbook used to de-risk production changes.
- Performance Engineering — Bottleneck analysis, tuning techniques, and benchmarking results that drove the measured efficiency gains.
- Lessons Learned — What worked, what we'd do differently, and the reusable patterns we now apply to similar modernization programs.
Get the full case study
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Full breakdown — challenge, approach, results & metrics.
