AI Agent · Customer ServiceTimeline: ~6–8 weeks
Smart Support Agent
Support agent — auto-answers FAQs, detects intent, and escalates to humans
AI AgentLLMSupport Automation
75%
Auto-resolution
-50%
Agent workload
Seconds
First response
Background
E-commerce support teams were overwhelmed by repetitive order and shipping queries, hurting conversion.
Core Challenge
Support teams drowned in repetitive order/shipping/refund tickets — slow replies raised costs and hurt conversion.
Our Approach
LLM + RAG: vectorized FAQs and policies, retrieve-then-answer, live order lookups, confidence-based human handoff, and log-driven improvement.
What We Did
- ·LLM-powered support agent for orders, logistics, and after-sales scenarios
- ·Connected to order systems and FAQ knowledge base for real-time replies
- ·Intent detection and human handoff strategy for complex cases
- ·Conversation logs and analytics dashboard for continuous improvement
Tech Stack
PythonLLM APIRAG / Vector DBNode.js
Outcome
75% auto-resolution rate, 50% less agent workload, first response in seconds.
Internal system · Not publicly availableAll case studiesRelated Service: SaaSRelated Scenario: AI Customer Service Agent Development