AI-Driven Lead Qualification & Automation Routing Pipeline
Built a fully automated system for an automation agency to solve the issue of messy inbound lead inquiries. The pipeline processes raw text, utilizes Gemini AI to instantly qualify client value based on scope and budget, syncs rows with a CRM database, and triggers real-time Slack alarms alongside hyper-personalized client email flows. Replaces hours of manual screening with a 13ms execution runtime.
10 Jul 2026
Keywords
AI Usage
In this project, AI was integrated directly into the core execution logic of the automation pipeline. I utilized a Google Gemini LLM via an n8n AI Agent node to dynamically read, analyze, and categorize unstructured inbound lead descriptions and estimated budgets. The AI acts as an intelligent triage engine, parsing complex user-submitted text and classifying the lead into "BIG CLIENT" or "SMALL CLIENT" tiers based on specific operational scale and project criteria. While Gemini made the high-level classification decisions, I handled the engineering manually—writing custom JavaScript nodes to sanitize the raw incoming form keys, cleaning up the LLM's string outputs into valid JSON data streams, and building the conditional routing architecture on the n8n canvas.
