//E-commerce · AI Automation
RAG support cutting ticket volume 58% for a DTC brand
A retrieval-augmented support system grounded in product docs and order data, deflecting 58% of tickets with cited, accurate answers and clean human handoff.
01The challenge
Support tickets scaled with revenue, response times slipped, and generic chatbots gave wrong answers that eroded trust.
02What we did
- 01Defined the knowledge sources, accuracy bar, and handoff rules.
- 02Prototyped retrieval quality on real customer questions.
- 03Forged a RAG system grounded in product and order data with citations.
- 04Hardened with evals and a clean escalation path to human agents.
//Results
The numbers
58%
tickets deflected
<1 min
first response
Cited
answers, not guesses
“It answers like our best rep — and admits when it should pass to a human.”
//Tech stack
- Claude
- pgvector
- Next.js
- Shopify
- n8n
//Next stepStart with a Blueprint.