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Retail

AI support assistant for a national retailer

A RAG-powered assistant deflected routine questions and handed the rest to agents with full context — cutting response times in half.

Client

A national retail chain (120M+ annual orders)

Timeline

10 weeks

Services

Custom AI & ML SoftwareWorkflow Automation

72%

of tickets auto-resolved

faster response times

10 wk

from kickoff to production

The challenge

The support team was drowning. Ticket volume had tripled in two years, response times were creeping past 12 hours, and agents spent most of their day answering the same order-status and returns questions instead of the ones that actually needed a human.

Our approach

  1. 1

    Ran a two-week discovery to map ticket types and pull the top 40 intents driving 80% of volume.

  2. 2

    Built a retrieval-augmented assistant grounded in their policies, order system, and help center — with guardrails and a confidence threshold that hands off to a human when unsure.

  3. 3

    Wired it into their existing helpdesk so resolved tickets close automatically and escalations arrive with full context attached.

“It actually holds up in production. The weekly demos meant zero surprises.”
Elena Vasquez — VP Engineering, Northwind

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