Google Gemini Chat Model and Hunter integration

How can you find your target market if you don't know what your product is. This simple philosophy changes the way we think about automated sales agents. Context changes everything. In this 4-part workflow, we start by creating a knowledge base that will act as context across the workflow. This context will guide and provide our AI Agents across the workflow to locate better leads and perform market research based on what the product actually offers. Use Case: Lead generation for Product-based Sales Tech Required Neon DB**: For storing Research and Lead Data. You can use Google sheets but it has a rate limiting problem. Google Serper**: As a web search tool for our AI. Google Drive**: For storing our knowledge base documents. Pinecone**: Vector DB for converting our knowledge base into context for AI. Hunter.io**: For finding emails for outreach. Email Client**: An email client, maybe gmail or anything that can send an email on your behalf. Gemini**: Our trusty AI LLM. Good to know All of the tools that I use in this workflow are either free or have an extremely generous free-tier. How it works We start by converting our knowledge base into context for AI. Take in the documents from Google drive and convert it into embeddings and store them in a vector store like Pinecone. This needs to be only run once, or whenever you have a new document in your knowledge base. Then we pass this context to an AI agent and tell it to generate search queries for locating companies that actually need my services. Then for each company that we've located, we determine the company staff that we need to reach out to for selling our product. This will be done by a combination of Google Serper and Hunter.io Once we have the list of employees and their emails, we start creating personalized emails based on the data we've collected for each of the employee and send them outreach emails.

AI-Powered Automated Proposal & Lead Management System This advanced n8n workflow automates the transition from "Raw Lead" to "Sent Proposal." By integrating Email Verification, Large Language Models (LLMs), and Document Automation, it eliminates manual data entry and ensures that every proposal sent is personalized, professional, and delivered to a verified address. 🛠️ How It Works Data Intake & Validation The workflow is triggered via a Webhook. Before any processing occurs, the data passes through the Hunter node, which performs a real-time email verification check. Smart Error Handling: An If Node evaluates the verification result. If the email is invalid or "risky," the workflow redirects to a Respond to Webhook node, providing immediate feedback to the source and preventing wasted API credits on downstream nodes. The AI Agent Layer Once validated, the data reaches the Set Fields node to be mapped for the AI. Custom Prompt Logic: The AI Agent node, powered by Google Gemini, contains a sophisticated custom prompt. This prompt acts as a "template engine," instructing the AI to take specific input variables (like client name, project scope, and budget) and output a clean, professional HTML structure. This allows for dynamic content generation that adapts to the unique context of every lead. Professional PDF Generation Instead of sending a plain text email, the workflow passes the AI-generated HTML to the PDF Generator API. This tool renders the code into a high-quality, brand-consistent PDF document ready for client viewing. Automated Delivery & CRM Logging Gmail Integration: The final PDF is automatically attached and sent to the verified email address with a personalized message. Google Sheets Logging: To ensure full visibility, the workflow appends a row to a Google Sheet, tracking the date, client details, and the status of the sent proposal. 📋 Requirements To run this workflow, you will need active accounts and API credentials for the following services: n8n Instance: (Self-hosted or Cloud). Hunter.io API: For the email verification node. Google Gemini API: To power the AI Agent and custom prompt. PDF Generator API: To convert the AI's HTML output into documents. Google Workspace Account: Required for the Gmail (Sending) and Google Sheets (Logging) nodes. ⚙️ How to Set Up Follow these steps to get the workflow operational: Import the Workflow: Download the JSON file and paste it into your n8n canvas. Configure Credentials: Connect your Hunter API key. Set up your Google Gemini credentials (via Google Cloud Console). Add your PDF Generator API key. Authenticate your Google Account (OAuth2) for Gmail and Google Sheets. Customize the AI Prompt: Open the AI Agent node. Under the "System Message" or "Prompt" section, adjust the HTML template to match your brand's style and the specific fields you want to include in your proposal. Map your Google Sheet: Open the Append row in sheet node and select the specific spreadsheet and worksheet where you want to log your leads. Test the Flow: Use the Webhook simulator (Example DATA) to send a test payload and verify that the PDF is generated and the email is sent correctly.