What is map-002-ai-lead-qualification?

This repository contains an automated workflow that helps sales teams figure out which potential customers are worth their time. When someone expresses interest in a product or service, that person is called a lead. Sales teams often have to manually review each lead to decide who should get immediate attention, which wastes valuable time. This project aims to solve that problem by using artificial intelligence to do the review automatically. The system works in a straightforward sequence. It starts by receiving information about a new lead through a webhook, which is a way for one program to send data to another in real time. The lead's information then goes to Google Gemini, an AI model made by Google. The AI analyzes the lead to understand how likely this person is to actually buy something, a concept called buying intent. After the AI finishes its analysis, a code step processes the results, and everything gets saved into a Google Sheets spreadsheet. The technology behind this workflow relies on a tool called n8n. Think of n8n as a digital connector that links different applications together without requiring much programming. In this setup, n8n coordinates the flow of information between the incoming lead data, the Google Gemini AI, and Google Sheets. Google Sheets serves as the storage place where all the results are recorded, making it easy for a sales team to review them later. For each lead that passes through the system, the workflow produces several pieces of information. It gives the lead a numerical score to indicate quality. It assigns a category to group similar leads together. It sets a priority level so the sales team knows who to contact first. It also provides a reason explaining why the AI made its decision. The repository suggests this workflow could be useful for software companies, AI startups, sales teams, and agencies. However, the README is sparse and does not provide installation instructions, configuration details, or code examples. Someone wanting to use this would need prior familiarity with n8n and how to connect it to Google services.