Automated AI Customer Support Workflow

Project Overview

This project automates email customer support using AI agents and vector retrieval to deliver instant, accurate responses to customer inquiries 24/7. Built on Veloce (n8n-based canvas), the workflow monitors incoming emails, classifies their intent, fetches verified business knowledge, and sends tailored replies—all in under one minute.

Key Problem Solved

Manual customer support leads to long response delays (often 3–6 hours during off-hours or busy workdays), leading to frustrated clients and lost revenue. This automation eliminates response lag while maintaining human-like accuracy.

Workflow Step-by-Step Architecture

Email Monitoring (Gmail Trigger): Continuously watches the inbox for incoming messages in real time.

Intent Classification (Text Classifier): Analyzes incoming emails to separate genuine customer support requests from promotional spam or irrelevant emails.

Knowledge Retrieval (Pinecone Vector Store + NVIDIA Nemotron Embeddings): The AI Agent pulls relevant context from stored company data (FAQs, pricing, policy documentation) to ground the response in factual business data.

AI Agent Processing (AI Agent + NVIDIA Nemotron Chat Model): Synthesizes the customer's query with the retrieved knowledge to draft a precise, personalized response.

Organization & Delivery (Add Label + Reply to Message): Tags the original email thread for organization and automatically sends the response back to the customer.

Technical Stack

Workflow Automation Platform: Veloce / n8n

LLM Engine: NVIDIA Nemotron Chat Model

Vector Store / RAG: Pinecone Vector Database with NVIDIA Nemotron Embeddings

Integrations: Gmail API

Core Benefits & ROI

Instant Response Time: Reduces customer wait times from hours to under 60 seconds.

24/7 Coverage: Provides instant replies during nights, weekends, and holidays without added staffing costs.

Factual Accuracy: Uses Retrieval-Augmented Generation (RAG) so the AI never hallucinates or provides wrong company data.