Fahmi Fahreza This workflow corresponds to n8n.io template #6418 — we link there as the canonical source.
This workflow follows the Airtable → Chainllm recipe pattern — see all workflows that pair these two integrations.
The workflow JSON
Copy or download the full n8n JSON below. Paste it into a new n8n workflow, add your credentials, activate. Full import guide →
{
"meta": {
"templateCredsSetupCompleted": true
},
"nodes": [
{
"id": "ba543316-f00d-452d-bdcb-929d264e2c30",
"name": "Google Gemini Chat Model",
"type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
"position": [
-464,
400
],
"parameters": {
"options": {},
"modelName": "models/gemini-2.5-flash-preview-04-17"
},
"credentials": {
"googlePalmApi": {
"name": "<your credential>"
}
},
"typeVersion": 1
},
{
"id": "7a05b84b-ed92-4e55-b932-390725dd9cb2",
"name": "Google Gemini Chat Model1",
"type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
"position": [
464,
400
],
"parameters": {
"options": {},
"modelName": "models/gemini-2.5-flash-preview-04-17"
},
"credentials": {
"googlePalmApi": {
"name": "<your credential>"
}
},
"typeVersion": 1
},
{
"id": "6cc4f324-dcfe-4e9f-8af3-34074306d37b",
"name": "Structured Output Parser",
"type": "@n8n/n8n-nodes-langchain.outputParserStructured",
"position": [
640,
416
],
"parameters": {
"jsonSchemaExample": "{\n\t\"score\": 100,\n\t\"fit_summary\": \"Los Angeles\"\n}"
},
"typeVersion": 1.2
},
{
"id": "b6b4e893-d011-43d8-9453-cb27fa1a54ab",
"name": "Watch for New Applications",
"type": "n8n-nodes-base.gmailTrigger",
"position": [
-1280,
16
],
"parameters": {
"simple": false,
"filters": {
"q": "has:attachment OR has:document"
},
"options": {
"downloadAttachments": true,
"dataPropertyAttachmentsPrefixName": "CV_"
},
"pollTimes": {
"item": [
{
"mode": "everyMinute"
}
]
}
},
"credentials": {
"gmailOAuth2": {
"name": "<your credential>"
}
},
"typeVersion": 1.2
},
{
"id": "57948245-8761-4b3d-9493-7ec14bdcbfcb",
"name": "Extract Job Code",
"type": "n8n-nodes-base.set",
"position": [
-624,
-224
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "4f8f7c3f-3f03-4b99-8332-c1131e7807b1",
"name": "=Job Code",
"type": "string",
"value": "={{ ($json.subject.match(/([A-Z]{2}-\\d{3})/) || [])[1] || null }}"
}
]
},
"includeOtherFields": true
},
"typeVersion": 3.4
},
{
"id": "026ad70e-f96a-4547-88cb-e95d07bb8d1a",
"name": "Find Job Post",
"type": "n8n-nodes-base.airtable",
"position": [
-224,
-224
],
"parameters": {
"base": {
"__rl": true,
"mode": "list",
"value": "apppwpxrdT85fG31V",
"cachedResultUrl": "https://airtable.com/apppwpxrdT85fG31V",
"cachedResultName": "UMKM"
},
"table": {
"__rl": true,
"mode": "list",
"value": "tblLM8M41XkSaTLxw",
"cachedResultUrl": "https://airtable.com/apppwpxrdT85fG31V/tblLM8M41XkSaTLxw",
"cachedResultName": "Job Posts"
},
"options": {},
"operation": "search",
"filterByFormula": "={Job Code} = '{{ $json[\"Job Code\"] }}'"
},
"credentials": {
"airtableTokenApi": {
"name": "<your credential>"
}
},
"typeVersion": 2.1,
"alwaysOutputData": true
},
{
"id": "31e468c3-3876-4789-bed7-ef9f274d4b0d",
"name": "Read CV (PDF) Text",
"type": "n8n-nodes-base.extractFromFile",
"position": [
-688,
272
],
"parameters": {
"options": {},
"operation": "pdf",
"binaryPropertyName": "CV_0"
},
"typeVersion": 1
},
{
"id": "995b95ca-ee4d-446a-886e-2500c34830c5",
"name": "AI CV Parser",
"type": "@n8n/n8n-nodes-langchain.informationExtractor",
"position": [
-464,
272
],
"parameters": {
"text": "=CV Text: {{ $json.text }}\n\nEmail Subject: {{ $('Watch for New Applications').item.json.subject }}",
"options": {
"systemPromptTemplate": "=You are a professional CV parsing and information extraction agent, specialized in structured data extraction for job applications.\nYour task is to extract only the **relevant attributes** from the applicant's CV text. Return the extracted information in **structured JSON format**, using the keys provided below.\nIf an attribute is not found or not confidently identifiable, you may **omit** that key from the response.\n\n### Extract the following attributes (if available):\n* `job_code`: the code of the job from the Email Subject\n* `name`: Full name of the applicant\n* `email`: Email address\n* `phone`: Phone number\n* `address`: Location or city (optional)\n* `education`: Highest education or relevant qualifications\n* `experience_years`: Estimated total years of relevant work experience\n* `skills`: List of relevant skills\n* `last_position`: Most recent job title or role\n* `last_company`: Most recent company worked at\n* `language`: List of languages spoken (optional)\n* `certifications`: Relevant certificates or training (optional)\n\n### Output Rules:\n* Only include fields that are clearly present in the CV and Email Subject.\n* Format your response as a clean, valid JSON object.\n* Do not include any explanations or extra text\u2014**only return JSON**."
},
"schemaType": "fromJson",
"jsonSchemaExample": "{\n \"job_code\": \"AB-001\",\n \"name\": \"Siti Nurhaliza\",\n \"email\": \"user@example.com\",\n \"phone\": \"+1234567890\",\n \"address\": \"Jakarta Selatan, Indonesia\",\n \"education\": \"Sarjana Teknik Industri, Universitas Indonesia\",\n \"experience_years\": 3.5,\n \"skills\": [\n \"Meracik Kopi\",\n \"Latte Art\",\n \"Customer Service\",\n \"Manajemen Waktu\"\n ],\n \"last_position\": \"Barista Senior\",\n \"last_company\": \"Kopi Kita Coffeehouse\",\n \"language\": [\n \"Bahasa Indonesia\",\n \"Inggris\"\n ],\n \"certifications\": [\n \"Sertifikat Barista dari SCA\",\n \"Pelatihan Latte Art Profesional\"\n ]\n}"
},
"typeVersion": 1.1
},
{
"id": "d36f4b59-cffc-4fa9-bb92-070630555882",
"name": "Combine Job & CV Data",
"type": "n8n-nodes-base.merge",
"position": [
32,
192
],
"parameters": {
"mode": "combine",
"options": {},
"advanced": true,
"mergeByFields": {
"values": [
{
"field1": "Job Code",
"field2": "output.job_code"
}
]
}
},
"typeVersion": 3.2
},
{
"id": "17a29a4a-c659-48ba-be25-2a38de28cc58",
"name": "AI Applicant Scorer",
"type": "@n8n/n8n-nodes-langchain.chainLlm",
"position": [
448,
192
],
"parameters": {
"text": "=You are given the following job requirements and a candidate's CV data.\nPlease evaluate the match and return a score from 1 to 100, along with a brief summary of your reasoning.\n\n---\n\n Job Post Data:\n- Job Title: {{ $json['Job Title'] }}\n- Required Skills: {{ $json['Required Skills'].join(', ') }}\n- Minimum Experience: {{ $json['Minimum Experience (Years)'] }} years\n- Job Description: {{ $json['Job Description'] }}\n\n---\n Applicant CV Data:\n- Name: {{ $json.output.name }}\n- Email: {{ $json.output.email }}\n- Phone: {{ $json.output.phone }}\n- Education: {{ $json.output.education }}\n- Experience: {{ $json.output.experience_years }} years\n- Skills: {{ $json.output.skills.join(', ') }}\n- Last Position: {{ $json.output.last_position }}\n- Last Company: {{ $json.output.last_company }}\n- Language: {{ $json.output.language.join(', ') }}\n- Certifications: {{ $json.output.certifications }}",
"batching": {},
"messages": {
"messageValues": [
{
"message": "=You are a professional job application evaluator and recruitment assistant. Your role is to assess the suitability of job applicants based on their CV data and compare it with the job's requirements. You must return a structured JSON response with the following keys: - `score`: A number between 1\u2013100 that reflects how well the applicant matches the job. - `fit_summary`: A short, clear explanation (max 2 sentences) of why you gave that score. Scoring is based primarily on: - Skill match (technical and soft skills) - Relevant experience (including job titles and industries) - Education or certification (if required) - Language and communication skills (optional) Be objective and consistent in your evaluations and use BAHASA INDONESIA. Only give high scores to applicants that strongly match the role requirements. Do not include any extra commentary \u2014 only return JSON."
}
]
},
"promptType": "define",
"hasOutputParser": true
},
"typeVersion": 1.7
},
{
"id": "ad1babe0-ccfb-4941-9b86-cf59ad6c77ca",
"name": "Save Applicant",
"type": "n8n-nodes-base.airtable",
"position": [
1136,
192
],
"parameters": {
"base": {
"__rl": true,
"mode": "list",
"value": "apppwpxrdT85fG31V",
"cachedResultUrl": "https://airtable.com/apppwpxrdT85fG31V",
"cachedResultName": "UMKM"
},
"table": {
"__rl": true,
"mode": "list",
"value": "tblkWxuaAvw0GmeCT",
"cachedResultUrl": "https://airtable.com/apppwpxrdT85fG31V/tblkWxuaAvw0GmeCT",
"cachedResultName": "Applications"
},
"columns": {
"value": {
"Notes": "={{ $json.output.fit_summary }}",
"Score": "={{ $json.output.score }}",
"Job Post": "={{ $('Combine Job & CV Data').item.json['Job Code'] }}",
"Email Address": "={{ $('Combine Job & CV Data').item.json.output.email }}",
"Applicant Name": "={{ $('Combine Job & CV Data').item.json.output.name }}",
"Years of Experience": 0
},
"schema": [
{
"id": "Application ID",
"type": "string",
"display": true,
"removed": true,
"readOnly": true,
"required": false,
"displayName": "Application ID",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Job Post",
"type": "array",
"display": true,
"removed": false,
"readOnly": false,
"required": false,
"displayName": "Job Post",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Applicant Name",
"type": "string",
"display": true,
"removed": false,
"readOnly": false,
"required": false,
"displayName": "Applicant Name",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Email Address",
"type": "string",
"display": true,
"removed": false,
"readOnly": false,
"required": false,
"displayName": "Email Address",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "CV File",
"type": "array",
"display": true,
"removed": false,
"readOnly": false,
"required": false,
"displayName": "CV File",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Parsed Skills",
"type": "array",
"display": true,
"options": [],
"removed": false,
"readOnly": false,
"required": false,
"displayName": "Parsed Skills",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Years of Experience",
"type": "number",
"display": true,
"removed": false,
"readOnly": false,
"required": false,
"displayName": "Years of Experience",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Score",
"type": "number",
"display": true,
"removed": false,
"readOnly": false,
"required": false,
"displayName": "Score",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Status",
"type": "options",
"display": true,
"options": [
{
"name": "Pending",
"value": "Pending"
},
{
"name": "Shortlisted",
"value": "Shortlisted"
},
{
"name": "Rejected",
"value": "Rejected"
}
],
"removed": false,
"readOnly": false,
"required": false,
"displayName": "Status",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Received At",
"type": "string",
"display": true,
"removed": true,
"readOnly": true,
"required": false,
"displayName": "Received At",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Raw Subject",
"type": "string",
"display": true,
"removed": false,
"readOnly": false,
"required": false,
"displayName": "Raw Subject",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Notes",
"type": "string",
"display": true,
"removed": false,
"readOnly": false,
"required": false,
"displayName": "Notes",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Auto ID",
"type": "string",
"display": true,
"removed": true,
"readOnly": true,
"required": false,
"displayName": "Auto ID",
"defaultMatch": false,
"canBeUsedToMatch": true
}
],
"mappingMode": "defineBelow",
"matchingColumns": [],
"attemptToConvertTypes": false,
"convertFieldsToString": false
},
"options": {},
"operation": "create"
},
"credentials": {
"airtableTokenApi": {
"name": "<your credential>"
}
},
"typeVersion": 2.1
},
{
"id": "25eb8342-394c-4165-9696-3d15097beae2",
"name": "Sticky Note1",
"type": "n8n-nodes-base.stickyNote",
"position": [
-2272,
-1104
],
"parameters": {
"width": 656,
"height": 1152,
"content": "## Automate CV Screening and Applicant Scoring from Gmail to Airtable with AI\n**This workflow automates the CV screening process using AI. It monitors a Gmail inbox for incoming applications, extracts and scores CVs based on job requirements stored in Airtable, and logs structured applicant data\u2014saving hours of manual work.**\n\n### How It Works\n1. **Trigger**\n Watches for new emails with attachments in a Gmail label.\n2. **Extract Data**\n * Extracts job code from the email subject (e.g., `FN-001`)\n * Extracts raw text from the attached CV (PDF)\n3. **AI Parsing**\n Uses Google Gemini to parse the CV and extract:\n * Name\n * Email\n * Years of experience\n * Skills\n4. **Job Lookup**\n Uses the extracted job code to retrieve job details from Airtable.\n5. **AI Scoring**\n * Compares applicant data with job requirements\n * Scores from 1\u2013100\n * Generates a brief reasoning summary (in Bahasa Indonesia)\n6. **Log to Airtable**\n Saves applicant data, score, and AI notes to the \"Applications\" table.\n\n### Setup Instructions\n1. **Prepare Airtable Base**\n * **Job Posts Table**\n * Columns: Job Code, Job Title, Required Skills, Minimum Experience, Job Description\n * **Applications Table**\n * Columns: Applicant Name, Email, Score, Notes\n * Include a linked field to the Job Posts table\n2. **Add Credentials in n8n**\n * Gmail\n * Google AI (Gemini)\n * Airtable\n3. **Configure Nodes**\n * **Trigger**: Set Gmail filter (e.g., `label:job-applications`)\n * **Extract Job Code**: Verify regex format, default is `([A-Z]{2}-\\d{3})`\n * **Airtable Nodes**: Select your base and table in:\n * \"Find Job Post...\"\n * \"Save Applicant...\"\n4. **Activate Workflow**\n * Save and enable the workflow\n * New applications will be processed automatically\n\n"
},
"typeVersion": 1
},
{
"id": "5782b22a-f17c-4dd3-bf59-c1929d3d70fe",
"name": "Sticky Note",
"type": "n8n-nodes-base.stickyNote",
"position": [
-1456,
-32
],
"parameters": {
"width": 368,
"height": 224,
"content": "## Watches for email with attachments"
},
"typeVersion": 1
},
{
"id": "7a32ee3d-51b3-48a5-88f6-6b1de399f318",
"name": "Sticky Note2",
"type": "n8n-nodes-base.stickyNote",
"position": [
-736,
-336
],
"parameters": {
"width": 688,
"height": 272,
"content": "## Fetch the Job Post In Airtable\nUses Regex to find a code like FN-001 in the email subject and use it to find the Job Post in Airtable\n\n\n"
},
"typeVersion": 1
},
{
"id": "17e071af-7f26-4c72-a528-9fa8cc026aca",
"name": "Sticky Note3",
"type": "n8n-nodes-base.stickyNote",
"position": [
-768,
176
],
"parameters": {
"width": 688,
"height": 352,
"content": "## Extract and Parse the CV Information\nGemini AI reads the CV text and extracts key info (name, skills, etc.) into structured JSON.\n\n\n"
},
"typeVersion": 1
},
{
"id": "8edcc4d8-58ec-422b-b6c2-df7b883f83cc",
"name": "Sticky Note4",
"type": "n8n-nodes-base.stickyNote",
"position": [
368,
64
],
"parameters": {
"width": 448,
"height": 496,
"content": "## Score Applicant with AI\nCompares the CV to the job details and generates a score (1-100) and a summary.\n\n\n"
},
"typeVersion": 1
}
],
"connections": {
"AI CV Parser": {
"main": [
[
{
"node": "Combine Job & CV Data",
"type": "main",
"index": 1
}
]
]
},
"Find Job Post": {
"main": [
[
{
"node": "Combine Job & CV Data",
"type": "main",
"index": 0
}
]
]
},
"Extract Job Code": {
"main": [
[
{
"node": "Find Job Post",
"type": "main",
"index": 0
}
]
]
},
"Read CV (PDF) Text": {
"main": [
[
{
"node": "AI CV Parser",
"type": "main",
"index": 0
}
]
]
},
"AI Applicant Scorer": {
"main": [
[
{
"node": "Save Applicant",
"type": "main",
"index": 0
}
]
]
},
"Combine Job & CV Data": {
"main": [
[
{
"node": "AI Applicant Scorer",
"type": "main",
"index": 0
}
]
]
},
"Google Gemini Chat Model": {
"ai_languageModel": [
[
{
"node": "AI CV Parser",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Structured Output Parser": {
"ai_outputParser": [
[
{
"node": "AI Applicant Scorer",
"type": "ai_outputParser",
"index": 0
}
]
]
},
"Google Gemini Chat Model1": {
"ai_languageModel": [
[
{
"node": "AI Applicant Scorer",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Watch for New Applications": {
"main": [
[
{
"node": "Extract Job Code",
"type": "main",
"index": 0
},
{
"node": "Read CV (PDF) Text",
"type": "main",
"index": 0
}
]
]
}
}
}
Credentials you'll need
Each integration node will prompt for credentials when you import. We strip credential IDs before publishing — you'll add your own.
airtableTokenApigmailOAuth2googlePalmApi
Pro
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About this workflow
Trigger Watches for new emails with attachments in a Gmail label. Extract Data Extracts job code from the email subject (e.g., ) Extracts raw text from the attached CV (PDF) AI Parsing Uses Google Gemini to parse the CV and extract: Name Email Years of experience Skills Job…
Source: https://n8n.io/workflows/6418/ — original creator credit. Request a take-down →
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