CASE STUDY
AI-Driven Claims & Complaint Resolution System
Challenge
A mid-size UK retail and distribution business needed to automate and standardise the handling of customer complaints and order discrepancies. Complaint resolution depended on manual investigation across CRM, ERP and warehouse systems, with inconsistent decisions, limited auditability, and heavy reliance on experienced staff during peak periods.
Solution
MPED designed and implemented an AI-driven operational model for complaint handling, combining advisory, architecture, integration and implementation. The solution connected CRM, ERP, WMS, email and internal knowledge sources through an API-led layer, added agent-based decision workflows, and introduced controlled validation and escalation paths so routine cases could be resolved faster without losing human oversight.
System functionality
- Automatic intake and classification of complaints
- Context building by aggregating data from CRM, ERP, WMS and communication systems
- AI-supported decision-making based on predefined business rules
- Automated response generation for standard cases
- Triggering returns, replacements and corrections
- Escalation to human operators when policy or confidence thresholds require review
- Full audit trail of decisions and actions
TECHNICAL SPECIFICATIONS
- Event-driven architecture using message queues
- Stateless execution of AI-driven workflows
- API-first integration across complaint, order and fulfilment systems
- Separation of execution and validation layers for controlled AI decisions
- Persistent state tracking for continuity, traceability and audit readiness
Technologies
- Microsoft Azure
- Azure Functions
- .NET (C#)
- REST APIs
- AI / LLM models via API
- Service Bus and event-driven architecture
APPLICATIONS
- Customer complaint resolution
- Order discrepancy handling
- Returns and replacement processing
- Operational exception handling
Results
- Significant reduction in manual processing effort
- Faster response times to customer complaints
- Improved consistency in decision-making
- Reduced dependency on senior staff for routine case resolution
- Increased process scalability without proportional headcount growth
- Better control, visibility and auditability across complaint handling
Summary
The AI-driven claims and complaint resolution system gave the client a structured, scalable process for handling complaints and order discrepancies across retail and distribution operations. By combining automated data gathering, controlled AI decision support and clear escalation logic, MPED helped reduce manual workload, improve response consistency and strengthen auditability without exposing the business to uncontrolled automation.