Modernizing Legacy Systems with LLMs: A Retail Case Study

NexaCode Engineering | January 20, 2025

Challenge

A national retail distributor was managing a legacy order-processing platform that had grown organically for more than a decade. On busy days, support reps spent 15–20 minutes resolving a single order exception because they had to search multiple systems for the right inventory, shipping and invoice details.

The search experience returned unrelated SKU matches, and the team relied on experience rather than consistent data. That led to delays, incorrect escalation decisions, and occasional customer callbacks.

Approach

We began with direct interviews across operations, fulfillment, and customer care. That surfaced three high-value exception categories: inventory dispute, address correction, and payment authorization problems.

• Mapped order, product, warehouse, and support logging sources into a single retrieval layer.
• Built a vector search index from actual order histories, product attributes, and exception notes.
• Created guided LLM prompts that suggested next actions while leaving final approval to the agent.

Implementation

The first release launched in six weeks. The system now surfaces an ordered list of the most relevant supporting documents, prior exception resolutions, and an LLM-generated recommendation for the agent to review.

From legacy order data to agent-facing LLM workflows and validated next-step guidance.

Results

• 80% reduction in average time-to-resolve for order exceptions.
• 35% faster agent onboarding through the conversational assistant.
• Established monitoring and evaluation gates for safe production rollout.