OmniAgent – Autonomous Multi-Agent Customer Support System (Canada)
AI & Machine Learning Verified Production Architecture

Project Overview

OmniAgent is an intelligent agentic customer resolution platform developed for an omnichannel retail corporation in Toronto, Canada. The system resolves complex customer inquiries, processes order returns, tracks shipments, and escalates edge cases with complete conversation context.

Client & Location

OmniRetail Group
Location: Toronto, ON, Canada
Industry: E-commerce & Retail

Challenges

  • Customer support wait times averaging over 45 minutes during flash sales and peak shopping periods.
  • High operational costs associated with scaling human support tiers across 24/7 timezones.
  • Repetitive inquiries regarding order status, returns, and inventory availability overburdening agents.

Solution

We developed a multi-agent orchestration framework (LangGraph) that coordinates specialized autonomous sub-agents: an Order Tracking Agent, an RMA Processing Agent, and a Product Recommender Agent, all tightly integrated with Shopify and Zendesk APIs.

Technologies Used

  • Python & LangGraph Multi-Agent Architecture
  • Claude 3.5 Sonnet & OpenAI GPT-4o
  • Zendesk & Shopify GraphQL APIs
  • Next.js Admin Analytics Dashboard

Results & Business Impact

  • 64% of first-touch support tickets resolved autonomously with zero human intervention.
  • Average resolution time plummeted from 45 minutes to under 30 seconds.
  • Customer Satisfaction (CSAT) rating increased from 3.7 to 4.8 out of 5.
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Project Details

Completed
Domain & Field AI & Machine Learning
Technologies Employed
AI AGENTS LANGCHAIN RAG VECTOR DB
Engagement & Delivery Dedicated Agile Pod
US & European Timezone Overlap
Client Confidentiality Bilateral Mutual NDA Signed
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