<aside>

Goal:

Automate email classification, response, and data extraction using AI to eliminate manual inbox management and turn emails into structured, actionable data.

Problem:

Managing a high volume of mixed emails (sales, job applicants, social media alerts, etc.) wastes time and leads to missed opportunities. Manual review is inefficient and unscalable for Web3 business development and HR.

Solution:

• Uses GPT to classify incoming emails by topic
• Generates auto-responses and drafts using AI
• Extracts structured data from job applications and logs it to Airtable
• Tags and manages emails directly in Gmail
• Eliminates manual inbox review for recruitment, sales, and personal messages

🔹 Step 1 – Trigger

New Email Received: A Gmail Trigger node activates the flow whenever a new message hits the inbox.

🔹 Step 2 – GPT Classification

Email Category Classifier (GPT):

The incoming email is sent to OpenAI GPT-4o to determine its category:

• Promotions
• Social Media
• Personal
• Sales
• Recruitment
• Miscellaneous

The result routes the email down the appropriate automation path.

🔹 Step 3 – Category-Based Handling

Each category has its own logic:

🔸 Promotions Path

• Tag as Promotions: Applies Gmail label
• Mark as Read: No further processing

🔸 Social Media Path

• Tag as Social Media
• GPT Summary Node: Summarizes the email content
• Log to Google Sheets: Stores summary with sender info and timestamp

🔸 Personal Path

• Tag as Personal
• GPT Draft Generator: Creates a custom response based on the message
• Save as Gmail Draft: Allows manual review before sending

🔸 Sales Path

• Tag as Sales
• GPT Auto-Responder: Crafts a reply to the sales pitch
• Send via Gmail: Auto-replies with a professional message

🔸 Recruitment Path

• Tag as Recruitment

• GPT Extractor: Parses candidate data (name, email, experience, LinkedIn, etc.)

• Function Node – Parse Candidate JSON for Airtable:

  Cleans and transforms GPT output for Airtable

• Create Record in Airtable:

  Logs applicant into Human Resources database

🔸 Miscellaneous Path

• Tag as Miscellaneous: No further action; archived for review if needed

Tools Used:

• n8n – Workflow automation engine
• OpenAI GPT-4o Mini – Email classification, summarization, auto-replies, and data extraction
• Gmail API – Email trigger and tagging
• Google Sheets – Social email logging
• Airtable – Candidate CRM system

Impact:

• Reduced inbox management time by 90%
• Handled 100% of initial candidate emails automatically
• Increased response speed to leads and recruiters
• Turned unstructured email chaos into structured HR and CRM pipelines
• Showcased multi-role AI deployment: classification, summarization, entity extraction, and decision-making

🧠Learnings:

• Learned how to parse GPT JSON outputs with Function nodes to integrate into external tools like Airtable.
• Understood the importance of structuring automation for scalability and clean data flow.
• Developed a clean logic tree using GPT not just for content creation, but also for classification and transformation.
• Discovered that clarity in node naming and visual structure is key when documenting automations for clients or hiring managers. </aside>

📂 Download & Explore the Workflow:

View GitHub Repository :

https://github.com/AlvLeoAI/inbox-intelligence-bot-n8n/blob/main/Inbox_Intelligence_Bot.json