AI Resume/CV Parser

Paste any resume. Get structured data in seconds. Powered by Google Gemini AI. Logs to Google Sheets automatically.

Live demo: ai-resumecv-parser.netlify.app Built by: Dev Pathak · linkedin.com/in/devpathak18

What Problem Does This Solve?

HR teams and hiring managers read hundreds of resumes manually every week. The same information — name, email, skills, experience, education — presented in hundreds of different formats. It is repetitive, slow, and error-prone.

This system eliminates that entirely.

Paste any resume — any format, any style — and the AI extracts every field, structures the data, and logs it to a Google Sheet automatically. What takes a human 5-10 minutes per resume takes this system under 10 seconds.

How It Works — The Full Pipeline

User pastes resume text
        |
        v
┌─────────────────────────┐
│  Netlify Frontend        │  ← JavaScript web form
│  ai-resumecv-parser      │    User hits "Parse Resume"
└────────────┬────────────┘
             |
             v  (POST request with resume JSON)
┌─────────────────────────┐
│  Make.com Webhook        │  ← Automation trigger
│  Receives resume text    │    Scenario activates instantly
└────────────┬────────────┘
             |
             v  (structured prompt + resume content)
┌─────────────────────────┐
│  Google Gemini 2.0 Flash │  ← AI model
│  Reads full resume       │    Extracts 13 data fields
│  Returns structured JSON │    Writes professional summary
└────────────┬────────────┘
             |
        ┌────┴────┐
        v         v
┌──────────┐  ┌──────────────────────┐
│  Google  │  │  Webhook Response     │
│  Sheets  │  │  Returns JSON to      │
│  New row │  │  frontend instantly   │
│  logged  │  │                      │
└──────────┘  └──────────────────────┘
                        |
                        v
              ┌─────────────────┐
              │  Frontend       │
              │  Displays result│
              │  in sections    │
              │  with skill tags│
              │  + score        │
              └─────────────────┘

Demo

[![Watch the demo] [https://www.loom.com/share/e58faf44b378481cb18fba305bbc2346]

Click the image above to watch a 2-minute walkthrough of the full pipeline running live.

In plain English:

You paste a resume
Make.com catches it and sends it to Gemini AI
Gemini reads the resume and extracts everything into JSON
Google Sheets gets a new row with all the candidate data
The website shows you the structured result instantly

What Gets Extracted

Gemini AI extracts 13 fields from any resume:

Field	What It Contains	Example
`name`	Full candidate name	Dev Pathak
`email`	Email address	dev@email.com
`phone`	Phone number	+91 **********
`location`	City and country	Bangalore, India
`linkedin`	LinkedIn profile URL	linkedin.com/in/devpathak18
`github`	GitHub profile URL	github.com/Devpathak18
`portfolio`	Portfolio website	www.example.com
`summary`	AI-written 2-3 sentence professional summary	Generated automatically
`skills`	Array of skills	Python, SQL, Gemini AI, Make.com
`experience`	Array of jobs with title, company, duration	AI Intern at XYZ Company
`education`	Array of degrees with institution and grade	B.Tech CSBS, Jain University
`certifications`	Array of certs with issuer and date	Gemini for Google Cloud, Google, 2026
`projects`	Array of projects with description and link	AI Email Automation, github.com/...

Sample output:

{
  "name": "Dev Pathak",
  "email": "devpathakpersonal@gmail.com",
  "phone": "+91 **********",
  "location": "Bangalore, India",
  "linkedin": "linkedin.com/in/devpathak18",
  "github": "github.com/Devpathak18",
  "portfolio": "wwww.example.com",
  "summary": "B.Tech CSBS student at Jain University building AI automation systems independently. Has deployed 4 live AI projects including email automation, research pipelines, and computer vision systems.",
  "skills": ["Python", "Make.com", "Google Gemini AI", "PyTorch", "SQL", "JavaScript"],
  "experience": [
    {
      "title": "AI Automation Developer",
      "company": "Independent",
      "duration": "May 2026 - Present",
      "description": "Built 4 live AI automation systems deployed in production"
    }
  ],
  "education": [
    {
      "degree": "B.Tech Computer Science and Business Systems",
      "institution": "Jain Deemed-to-be University",
      "year": "2028",
      "grade": "8.00 CGPA"
    }
  ],
  "certifications": [
    {
      "name": "Gemini for Google Cloud",
      "issuer": "Google",
      "date": "March 2026"
    }
  ],
  "projects": [
    {
      "name": "AI Email Automation Pipeline",
      "description": "Gmail to Gemini AI to Google Sheets to Telegram",
      "link": "github.com/Devpathak18/email-ai-automation"
    }
  ]
}

Live Features on the Frontend

Structured Sections

Every extracted field is displayed in a clean organised section — not a raw JSON dump. Each section has an icon, title, and the extracted data formatted for easy reading.

Skill Tags

Skills are displayed as visual pill-shaped tags — the same way LinkedIn and job portals show them. Easy to scan at a glance.

[Python]  [Make.com]  [Gemini AI]  [PyTorch]  [SQL]  [JavaScript]

Profile Completeness Score

After extraction, the system calculates what percentage of the 13 fields were successfully found in the resume. Shows as a progress bar.

Profile Completeness: 92% — 12 of 13 fields found

AI-Generated Summary

Even if the resume has no summary section, Gemini AI writes a professional 2-3 sentence summary based on the rest of the content.

Tech Stack

Layer	Tool	Why This Tool
Frontend	HTML + CSS + JavaScript	Lightweight, no framework needed, deploys anywhere
Hosting	Netlify	Free static hosting, HTTPS, instant deploy by drag and drop
Automation	Make.com	No-code workflow orchestration — connects all services via webhooks
AI Model	Google Gemini 2.0 Flash	Fast, accurate, free tier handles 1,500 requests per day
Storage	Google Sheets	Free, shareable, searchable HR database out of the box
API	Gemini API via Make.com	No backend server needed — Make.com makes the API call

Why no backend server? The entire system uses Make.com as the middleware. The HTML frontend sends a webhook to Make.com → Make.com calls Gemini API → Make.com logs to Sheets → Make.com responds to the frontend. Zero server management, zero deployment complexity.

Repository Structure

ai-resumecv-parser/
├── README.md                  ← You are here
├── ai-resume-parser.html      ← Complete frontend (one file)
├── make-blueprint.json        ← Import into Make.com (one click)
└── .env.example               ← Configuration reference

Setup Guide

What You Need

Make.com account (free tier works)
Google account (for Gemini API + Google Sheets)
Netlify account (free — for hosting)
Gemini API key (free — from aistudio.google.com)

Step 1 — Get Gemini API Key

Go to aistudio.google.com
Click Get API Key → Create API Key
Copy the key — keep it safe

Step 2 — Set Up Google Sheets

Create a new Google Sheet with these column headers in Row 1:

Timestamp | Name | Email | Phone | Location | Skills | Full JSON

Step 3 — Import Make.com Blueprint

Go to make.com → Create New Scenario
Click the three dots menu → Import Blueprint
Select make-blueprint.json from this repo
Update the Google Sheets module → connect your Google account → select your sheet
Update the Gemini module → connect your Google account
Copy the webhook URL from Module 1

Step 4 — Configure Frontend

Open ai-resume-parser.html → find this line:

const WEBHOOK_URL = 'YOUR_MAKE_WEBHOOK_URL';

Replace with your Make.com webhook URL.

Step 5 — Deploy to Netlify

Go to netlify.com
Drag and drop ai-resume-parser.html
Get your live URL instantly

Step 6 — Turn On and Test

In Make.com → toggle scenario ON
Go to your Netlify URL
Paste any resume text
Click Parse Resume
Watch the result appear and check your Google Sheet for the new row

Challenges I Faced and Fixed

Challenge 1 — HTTP Module JSON Error

Problem: Make.com's raw HTTP module kept throwing InvalidConfigurationError for the JSON body containing the Gemini prompt with special characters.

Fix: Switched from the raw HTTP module to Make.com's native Google Gemini module — it handles all JSON serialisation internally without manual body formatting.

Challenge 2 — CORS Error on Local File

Problem: Opening the HTML file locally (file://) caused browsers to block the fetch request to Make.com's webhook.

Fix: Deployed to Netlify — requests from HTTPS domain pass CORS checks without any server-side headers needed.

Challenge 3 — Wrong Gemini Model Name

Problem: gemini-1.5-flash returned a 404 — model not found in API version v1beta.

Fix: Updated to gemini-2.0-flash — the current supported model as of 2026.

Challenge 4 — Module ID Reference Error

Problem: After switching from HTTP to Gemini module, all downstream modules were still referencing the old module ID number.

Fix: Remapped all variable references using Make.com's variable picker to the correct new module IDs.

Cost to Run This

Service	Free Tier	Cost
Make.com	1,000 operations/month	Rs. 0
Google Gemini API	1,500 requests/day	Rs. 0
Google Sheets	Unlimited rows	Rs. 0
Netlify	100GB bandwidth/month	Rs. 0
Total	1,500 resumes/day	Rs. 0

Related Projects

This is Project 4 in an ongoing AI automation series:

Project	What It Does	Link
AI Email Automation	Gmail → Gemini AI → Google Sheets → Telegram	github.com/Devpathak18/email-ai-automation
AI Research Pipeline	Any topic → Local LLM → 7-step guide → Google Docs	github.com/Devpathak18/ai-research-automation
AI Product Intelligence	CLIP-based reverse search + duplicate detection + recommendations	github.com/Devpathak18/ai-product-intelligence-system
AI Resume Parser	Resume text → Gemini AI → structured data → Google Sheets	This repo

Author

Dev Pathak B.Tech Computer Science and Business Systems (CSBS) Program co-designed with Tata Consultancy Services

Open to remote internships in AI automation, data analytics, and machine learning.

Star This Repo

If this project helped you or gave you ideas — star the repo. It helps others find it.

Name		Name	Last commit message	Last commit date
AI Resume Parser.blueprint.json		AI Resume Parser.blueprint.json
AI Resume Parser.html		AI Resume Parser.html
README.md		README.md

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Repository files navigation

AI Resume/CV Parser

What Problem Does This Solve?

How It Works — The Full Pipeline

Demo

What Gets Extracted

Live Features on the Frontend

Structured Sections

Skill Tags

Profile Completeness Score

AI-Generated Summary

Tech Stack

Repository Structure

Setup Guide

What You Need

Step 1 — Get Gemini API Key

Step 2 — Set Up Google Sheets

Step 3 — Import Make.com Blueprint

Step 4 — Configure Frontend

Step 5 — Deploy to Netlify

Step 6 — Turn On and Test

Challenges I Faced and Fixed

Challenge 1 — HTTP Module JSON Error

Challenge 2 — CORS Error on Local File

Challenge 3 — Wrong Gemini Model Name

Challenge 4 — Module ID Reference Error

Cost to Run This

Related Projects

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AI Resume/CV Parser

What Problem Does This Solve?

How It Works — The Full Pipeline

Demo

What Gets Extracted

Live Features on the Frontend

Structured Sections

Skill Tags

Profile Completeness Score

AI-Generated Summary

Tech Stack

Repository Structure

Setup Guide

What You Need

Step 1 — Get Gemini API Key

Step 2 — Set Up Google Sheets

Step 3 — Import Make.com Blueprint

Step 4 — Configure Frontend

Step 5 — Deploy to Netlify

Step 6 — Turn On and Test

Challenges I Faced and Fixed

Challenge 1 — HTTP Module JSON Error

Challenge 2 — CORS Error on Local File

Challenge 3 — Wrong Gemini Model Name

Challenge 4 — Module ID Reference Error

Cost to Run This

Related Projects

Author

Star This Repo

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