AI Lead Qualification System
Self-built automation demo — not a client project.
An AI-powered lead processing system that receives enquiries, evaluates buying intent, assigns a qualification score and stores prioritized leads automatically.
Overview
A public lead form submits an enquiry that is qualified by an AI model in real time and stored in a database, visible on an internal dashboard.
Problem
Every inbound enquiry looks the same until someone reads it — high-intent leads can sit behind low-intent ones with no way to tell them apart at a glance.
Solution
An AI model scores buying intent against defined criteria the moment an enquiry arrives, before a human ever opens it.
Architecture
How the system is wired together
Workflow
What happens on submission
- 1The lead form submits name, email, company, and a message to an n8n webhook.
- 2n8n sends the enquiry to an OpenRouter-hosted AI model with qualification criteria.
- 3The model returns a structured qualification — label, score, and reason.
- 4The lead and its qualification are stored in Supabase, visible on an internal dashboard.
AI decision logic
A structured qualification, not a guess
The model returns a fixed schema — a label (hot, warm, cold), a numeric score, and a one-sentence reason — so the result is consistent and usable by the dashboard, independent of the exact wording the model produces.
Demonstration data
HotScore: 88
Reason: Strong buying intent and clear requirement.
Technology
Testing
Verified end-to-end
- Form submission through to a stored, qualified lead
- Structured output validated against the qualification schema on every response
- Dashboard filtering and stats checked against seeded and live data
Demo
Self-built demonstration, not a live client system
This project is a working prototype built to demonstrate the pattern end-to-end. All example data shown above is demonstration data, not a real enquiry.