Score WhatsApp PDF resumes with OpenAI GPT-4o-mini and Supabase

Description

WhatsApp Resume Ranking Bot — AI-Powered Career Score via PDF Upload

Let job seekers check their resume strength directly on WhatsApp — no app, no sign-up, no friction. Users send a keyword, answer 2 quick questions, upload their PDF resume, and receive a personalized career score, ATS feedback, and rejection analysis in under 60 seconds.

Who is this for?

Career coaches, job portals, HR-tech startups, or recruitment agencies who want to offer a self-serve resume evaluation tool directly inside WhatsApp — where their audience already is.

What this workflow does

Listens for incoming WhatsApp messages via the WhatsApp Business Cloud API
Manages multi-turn conversation state in Supabase — tracks each user's progress through the flow (idle → name → role → resume → processing)
Guides the user step-by-step to provide their name, target job role, and PDF resume
Downloads the resume PDF from WhatsApp's media server using the Business API
Extracts resume text for analysis
Runs a Scoring Engine that calculates a career score (0–100) based on resume content and target role
Calls OpenAI (GPT-4o-mini) in parallel to generate rejection reasons and actionable improvement tips
Merges both results and formats a final WhatsApp message
Sends the personalized report back to the user — score, weaknesses, and what to fix

Prerequisites

A WhatsApp Business Cloud API account (Meta Developer App in Live mode)
A Supabase project with a whatsapp_sessions table
An OpenAI API key (GPT-4o-mini recommended)
A self-hosted n8n instance or n8n Cloud

Supabase table setup

Create a table called whatsapp_sessions with these columns:

| Column | Type | Notes |
|---|---|---|
| phone | text | Primary key / unique |
| state | text | Conversation state (IDLE, WAITING_NAME, etc.) |
| name | text | User's name |
| target_role | text | Job role they're targeting |
| started_at | timestamptz | Session start time |
| updated_at | timestamptz | Last activity timestamp |

Setup steps

Connect WhatsApp Business API credentials in n8n (Meta App token + Phone Number ID)
Connect OpenAI credentials in n8n
Update the Supabase URL and API key inside the Conversation State Manager Code node
Replace YOUR_PHONE_NUMBER_HERE in the Send nodes with your WhatsApp Phone Number ID
Set up Meta webhook pointing to your n8n WhatsApp Trigger URL, subscribed to messages
Activate the workflow — users can now send CHECK MY RANK to trigger the bot

Conversation flow
User: CHECK MY RANK
Bot: Intro + "Type YES to start"
User: YES
Bot: "What's your full name?"
User: Rahul Sharma
Bot: "Which job role are you targeting?"
User: Data Analyst
Bot: "Upload your resume as a PDF"
User: [uploads PDF]
Bot: "Analyzing... hang tight 🔍"
Bot: [sends career score + rejection reasons + tips]

Customization

Modify the Scoring Engine Code node to adjust how the score is calculated (weights for skills, experience, formatting, etc.)
Edit the OpenAI prompt to change the tone or depth of feedback
Add a Supabase insert after analysis to log all submissions for your own analytics
Extend the flow to offer a paid detailed report or booking link after the free score

⚠️ Important notes

The WhatsApp App must be in Live mode (not sandbox) to receive messages from non-whitelisted numbers — requires completing Meta Business Verification
Only PDF resumes are supported; DOCX files are rejected with a helpful prompt
Session state persists in Supabase, so users can resume mid-flow if they get disconnected
The bot handles concurrent users independently via phone number as the session key