Complete B2B sales pipeline: Apollo lead gen, Mailgun outreach & AI reply management
✉️ AI-Powered 3-Step B2B Pipeline — Lead Gen → Cold Outreach → AI Drafted Email Management
Automate your outbound workflow from prospecting to AI-generated reply drafts in Gmail — all fully integrated with your database.
Ideal for SDRs, founders, and growth agencies who want speed, personalization, and control without losing human review.
📌 Example: From a verified lead list to a qualified opportunity — fully tracked, classified, and pre-drafted with this automation.
🚀 What This Workflow Does
Step 1 — Lead Generation
- Import leads from Apollo.
- Enrich and verify emails.
- Store results in Supabase/Postgres,
Step 2 — Cold Outreach
- Send 3 step personalized sequences via Mailgun/SendGrid.
- Track delivery, opens, replies, and bounces directly in your DB.
Step 3 — Email Management (AI Drafts)
- Process only incoming Gmail messages from contacts in your DB.
- Generate personalized reply drafts, label threads, update lead status, and alert your team via Slack/Telegram.
🔗 Integrated Services
- Database: Supabase/Postgres
- Outbound Email: Mailgun / SendGrid
- Inbound Email & Drafts: Gmail (OAuth2)
- AI Models: OpenAI / Anthropic (JSON mode for classification + drafting)
- Alerts: Slack / Telegram (optional)
💼 What You Get
- Detailed setup guide
- Fully connected 3-step pipeline in n8n
- Ready-to-use database schema
- Pre-built AI prompts for intent classification and professional replies
📥 Perfect For
- SDR teams doing targeted outbound
- Agencies managing multiple client campaigns
- Founders building scalable outbound systems
- Sales ops needing a no-risk, review-first reply process
💡 Why You’ll Love It
This isn’t just another outreach template — it’s a full sales engine.
From verified leads to AI-drafted replies, every action is logged, tracked, and controlled for maximum conversions without sacrificing oversight.
n8n AI-Powered B2B Sales Pipeline: Apollo Lead Gen, Mailgun Outreach, and AI Reply Management
This n8n workflow automates a comprehensive B2B sales pipeline, from lead generation and outreach to intelligent AI-driven reply management. It leverages various services to streamline the entire sales process, ensuring timely follow-ups and personalized communication.
What it does
This workflow orchestrates the following key steps:
- Scheduled Lead Generation: Periodically queries a Supabase database (or a Postgres database, depending on configuration) to fetch new leads.
- Email Outreach: For each new lead, it sends a personalized email using Mailgun.
- Lead Status Management: Updates the lead status in Supabase (or Postgres) to "outreach sent".
- AI Reply Monitoring (Gmail/Telegram):
- Option 1 (Gmail): Listens for incoming email replies via a Gmail trigger.
- Option 2 (Telegram): Listens for incoming messages via a Telegram trigger, potentially for manual intervention or specific commands.
- AI Reply Analysis: When a reply is received, an AI Agent (powered by OpenAI or Anthropic Chat Models) analyzes the email content to understand the sentiment and intent.
- Structured Output Parsing: The AI's analysis is then parsed into a structured format using a Structured Output Parser.
- Reply Categorization: Based on the AI's analysis, the workflow categorizes the reply (e.g., "positive," "negative," "needs follow-up").
- Conditional Actions:
- Positive Reply: If the reply is positive, it might trigger a notification (e.g., to Telegram) or update the lead status in the database.
- Negative Reply: If the reply is negative, it might update the lead status and potentially stop further outreach.
- Needs Follow-up/Other: For other replies, it might trigger a specific follow-up action, potentially involving a human-in-the-loop (HITL) process via Telegram.
- Database Updates: Continuously updates lead records in the database (Supabase/Postgres) with the latest communication status, AI analysis, and next steps.
- Delay/Wait: Incorporates wait steps to manage the timing of outreach and follow-ups.
Prerequisites/Requirements
To use this workflow, you will need accounts and API keys for the following services:
- Supabase or Postgres Database: To store and manage your leads.
- Mailgun: For sending outbound emails.
- Gmail Account: If you choose to monitor email replies via Gmail.
- Telegram Bot: If you choose to monitor replies or receive notifications via Telegram.
- OpenAI API Key or Anthropic API Key: For the AI Agent to analyze email replies.
- n8n Instance: A running n8n instance to host and execute the workflow.
Setup/Usage
- Import the Workflow: Download the JSON content and import it into your n8n instance.
- Configure Credentials:
- Add your Supabase or Postgres credentials to the respective nodes.
- Add your Mailgun credentials.
- Add your Gmail credentials (if using the Gmail trigger/node).
- Add your Telegram Bot credentials (if using the Telegram trigger/node).
- Add your OpenAI or Anthropic credentials for the AI Agent and Chat Model nodes.
- Database Schema: Ensure your Supabase/Postgres database has a table for leads with relevant fields (e.g.,
email,status,last_outreach_date,ai_analysis,reply_category). - Customize AI Prompts: Adjust the prompts in the "AI Agent" and "Structured Output Parser" nodes to fine-tune the AI's analysis and categorization of email replies according to your specific needs.
- Configure Schedule Trigger: Set the desired schedule for the "Schedule Trigger" node to define how often new leads are fetched and outreach is initiated.
- Activate the Workflow: Once all credentials and configurations are set, activate the workflow in your n8n instance.
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Modify and adapt freely for your business needs. --- Version: 1.0 Last Updated: October 2025 Compatibility: n8n v1.0+ (Cloud & Self-Hosted), Claude API v2024-10+
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Track personal finances in Google Sheets with AI agent via Slack
Who's it for This workflow is perfect for individuals who want to maintain detailed financial records without the overhead of complex budgeting apps. If you prefer natural language over data entry forms and want an AI assistant to handle the bookkeeping, this template is for you. It's especially useful for: People who want to track cash and online transactions separately Anyone who lends money to friends/family and needs debt tracking Users comfortable with Slack as their primary interface Those who prefer conversational interactions over manual spreadsheet updates What it does This AI-powered finance tracker transforms your Slack workspace into a personal finance command center. 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How it works Scheduled Daily Check-in (11 PM) Fetches current balances from Google Sheets Retrieves all active debts Formats and sends a Slack message with balance summary Prompts you to share the day's transactions AI Agent Transaction Processing When you mention the bot in Slack: Phase 1: Parse & Analyze Extracts amount, payment type (cash/online), category (food, travel, etc.) Identifies transaction type (expense, income, borrowed, lent, repaid) Stores conversation context in PostgreSQL memory Phase 2: Calculate & Preview Reads current balances from Google Sheets Calculates new balances based on transactions Shows formatted preview with projected changes Waits for your approval ("yes"/"no") Phase 3: Update Database (only after approval) Logs transactions with unique IDs and timestamps Updates debt records with person names and status Recalculates and stores new balances Handles debt lifecycle (Active → Settled) Phase 4: Confirmation Sends success message with updated balances Shows active debts summary Includes logging timestamp Requirements Essential Services: n8n instance (self-hosted or cloud) Slack workspace with admin access Google account Google Gemini API key PostgreSQL database Recommended: Claude AI model (mentioned in workflow notes as better alternative to Gemini) How to set up Google Sheets Setup Create a new Google Sheet with three tabs named exactly: Balances Tab: | Date | CashBalance | OnlineBalance | Total_Balance | |------|--------------|----------------|---------------| Transactions Tab: | TransactionID | Date | Time | Amount | PaymentType | Category | TransactionType | PersonName | Description | Added_At | |----------------|------|------|--------|--------------|----------|------------------|-------------|-------------|----------| Debts Tab: | PersonName | Amount | Type | Datecreated | Status | Notes | |-------------|--------|------|--------------|--------|-------| Add header rows and one initial balance row in the Balances tab with today's date and starting amounts. Slack App Setup Go to api.slack.com/apps and create a new app Under OAuth & Permissions, add these Bot Token Scopes: app_mentions:read chat:write channels:read Install the app to your workspace Copy the Bot User OAuth Token Create a dedicated channel (e.g., personal-finance-tracker) Invite your bot to the channel Google Gemini API Visit ai.google.dev Create an API key Save it for n8n credentials setup PostgreSQL Database Set up a PostgreSQL database (you can use Supabase free tier): Create a new project Note down connection details (host, port, database name, user, password) The workflow will auto-create the required table n8n Workflow Configuration Import the workflow and configure: A. Credentials Google Sheets OAuth2: Connect your Google account Slack API: Add your Bot User OAuth Token Google Gemini API: Add your API key PostgreSQL: Add database connection details B. Update Node Parameters All Google Sheets nodes: Select your finance spreadsheet Slack nodes: Select your finance channel Schedule Trigger: Adjust time if you prefer a different check-in hour (default: 11 PM) Postgres Chat Memory: Change sessionKey to something unique (e.g., financetrackeryour_name) Keep tableName as n8nchathistory_finance or rename consistently C. Slack Trigger Setup Activate the "Bot Mention trigger" node Copy the webhook URL from n8n In Slack App settings, go to Event Subscriptions Enable events and paste the webhook URL Subscribe to bot event: app_mention Save changes Test the Workflow Activate both workflow branches (scheduled and agent) In your Slack channel, mention the bot: @YourBot ₹100 cash snacks Bot should respond with a preview Reply "yes" to approve Verify Google Sheets are updated How to customize Change Transaction Categories Edit the AI Agent's system message to add/remove categories. Current categories: travel, food, entertainment, utilities, shopping, health, education, other Modify Daily Check-in Time Change the Schedule Trigger's triggerAtHour value (0-23 in 24-hour format). Add Currency Support Replace ₹ with your currency symbol in: Format Daily Message code node AI Agent system prompt examples Switch AI Models The workflow uses Google Gemini, but notes recommend Claude. To switch: Replace "Google Gemini Chat Model" node Add Claude credentials Connect to AI Agent node Customize Debt Types Modify AI Agent's system prompt to change debt handling logic: Currently: IOwe and TheyOwe_Me You can add more types or change naming Add More Payment Methods Current: cash, online To add more (e.g., credit card): Update AI Agent prompt Modify Balances sheet structure Update balance calculation logic Change Approval Keywords Edit AI Agent's Phase 2 approval logic to recognize different approval phrases. Add Spending Analytics Extend the daily check-in to calculate: Weekly/monthly spending summaries Category-wise breakdowns Use additional Code nodes to process transaction history Important Notes ⚠️ Never trigger with normal messages - Only use app mentions (@botname) to avoid infinite loops where the bot replies to its own messages. 💡 Context Awareness - The bot remembers conversation history, so you can reference "yesterday", "last week", or previous transactions naturally. 🔒 Data Privacy - All your financial data stays in your Google Sheets and PostgreSQL database. The AI only processes transaction text temporarily. 📊 Backup Regularly - Export your Google Sheets periodically as backup. --- Pro Tips: Start with small test transactions to ensure everything works Use consistent person names for debt tracking The bot understands various formats: "₹500 cash food" = "paid 500 rupees in cash for food" You can batch transactions in one message: "₹100 travel, ₹200 food, ₹50 snacks"