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Automated Multi-Agent AI Support & Lead Triage Pipeline
Are your high-ticket clients waiting hours for an email response? This intelligent multi-agent n8n workflow instantly screens, analyzes, and responds to customer emails in real-time, utilizing advanced RAG (Retrieval-Augmented Generation) to deliver human-like support instantly.
Project Overview:
This is an enterprise-grade AI automation system designed to eliminate manual customer support queues. Instead of simple auto-replies, it uses a multi-agent routing structure combined with a dynamic knowledge base to handle complex inquiries autonomously.
How It Works (Under the Hood):
Instant Inbound Triage: A Gmail Trigger catches incoming emails instantly, extracting raw content for processing.
AI Intent Classification: An initial OpenAI model acts as a gatekeeper, analyzing the email to determine if it is a valid customer support request or irrelevant noise.
Conditional Routing: An advanced router splits the path: non-support emails receive a polite automated Telegram update, while actual support tickets are routed to the main AI engine.
Context-Aware AI Agent: The core Customer Support Agent is equipped with an OpenAI Chat Model, conversational memory, and a custom Vector Store Tool.
Pinecone RAG Integration: The agent queries a Pinecone Vector Database (powered by OpenAI Text Embeddings) to fetch real-time, accurate company documentation and context, eliminating hallucinations.
Automated Action & Response: Once the resolution is drafted, the system automatically creates a draft in Gmail for review and sends an instant internal notification via Telegram.
Why This Wins Clients (The Value Pitch):
Zero Hallucinations: Connected to a live vector database (Pinecone) so the AI only speaks from approved company data.
Reduced Overhead: Cuts down customer support response times from hours to under 60 seconds.
Production-Ready Architecture: Designed with modern n8n AI sub-nodes, structured tools, and modular scaling capabilities.
For anyone curious about the architecture under the hood:
Orchestration: n8n (Self-hosted for unlimited scale)
LLM: OpenAI GPT models
Memory & Vector DB: Pinecone Store for dynamic contextual injection
Routing: Native n8n conditional logic to isolate internal alerts...
The network for creativity
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A few weeks ago one of my bigger AI clients came back with a new scope focused on improving parts of their website experience 🚀
What you see here is the updated direction for the homepage and first screens. Compared to the previous version, this one feels way more functional, easier to understand, and overall much closer to the actual level of the product and business itself.
During the process I focused a lot on product-oriented thinking, user behavior, clarity, structure, and small marketing-focused details through the design instead of just trying to make things look flashy.
And thankfully, the client ended up approving the direction really fast 👀
There’s actually a lot more cool stuff inside this project — more pages, details, interactions, and updates across the whole experience.
Would be curious to know, would you guys like to see a full case study with more mockups, videos, and breakdowns from this one?
This direction feels significantly stronger.
The balance between clarity, product positioning, and visual execution is really well handled.
You can tell the decisions were driven by user experience and business goals, not just aesthetics.
Excited to see the full case study and interaction breakdowns
Excellent job!
Designing interactive websites every day for 30 days.
This build features Scroll-Pinned Rotational Stacking: a custom GSAP engine where sections rotate into place and stack with depth recession and velocity-reactive particle debris.
Open for custom website projects 💥
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