ERPNext AI 후보자 선별 자동화
고급
이것은Finance, AI분야의자동화 워크플로우로, 39개의 노드를 포함합니다.주로 If, Set, Code, Merge, Switch 등의 노드를 사용하며인공지능 기술을 결합하여 스마트 자동화를 구현합니다. ERPNext의 AI 기반 후보자 선별 자동화
사전 요구사항
- •HTTP Webhook 엔드포인트(n8n이 자동으로 생성)
- •대상 API의 인증 정보가 필요할 수 있음
- •Google Gemini API Key
사용된 노드 (39)
워크플로우 미리보기
노드 연결 관계를 시각적으로 표시하며, 확대/축소 및 이동을 지원합니다
워크플로우 내보내기
다음 JSON 구성을 복사하여 n8n에 가져오면 이 워크플로우를 사용할 수 있습니다
{
"meta": {
"instanceId": "e4f78845dfed9ddcfba1945ae00d12e9a7d76eab052afd19299228ce02349d86"
},
"nodes": [
{
"id": "a8b14ffd-4a8b-4a3d-ba54-5997197e5457",
"name": "메모4",
"type": "n8n-nodes-base.stickyNote",
"position": [
-2880,
340
],
"parameters": {
"color": 6,
"width": 429.96763122593137,
"height": 322,
"content": "### Get Apprropraite Data\nThese Nodes are to extract only the Required Data from the Webhook Node"
},
"typeVersion": 1
},
{
"id": "c8ae8766-3942-4b8d-8815-9e96ab9dc1de",
"name": "메모6",
"type": "n8n-nodes-base.stickyNote",
"position": [
-840,
340
],
"parameters": {
"color": 5,
"width": 677,
"height": 660,
"content": "### N8N has the Node to convert PDF to Text, but PDF should be converted from Text. Scanned Image PDF will not be converted. \n\nYou can use ohter nodes here to convert word file to text or JPG to Text, possiblities are limitless."
},
"typeVersion": 1
},
{
"id": "529f5756-c1a2-4c41-8245-38164543eb8e",
"name": "메모",
"type": "n8n-nodes-base.stickyNote",
"position": [
-1334.2232779572741,
340
],
"parameters": {
"color": 7,
"width": 477.2230145794152,
"height": 648.5051458745238,
"content": "### Download the File.\nIf you are using S3 to Upload attachments you can use S3 node here to download the attachment\n"
},
"typeVersion": 1
},
{
"id": "101c6544-d319-495d-a14f-e180f51be1f0",
"name": "코드",
"type": "n8n-nodes-base.code",
"position": [
-2840,
480
],
"parameters": {
"jsCode": "// Loop over input items and add a new field called 'myNewField' to the JSON of each one\nfor (const item of $input.all()) {\n item.json.myNewField = 1;\n}\n\nreturn $input.all();"
},
"typeVersion": 2
},
{
"id": "5d0a1090-9be9-41e1-9a15-26bd6498fd95",
"name": "메모2",
"type": "n8n-nodes-base.stickyNote",
"position": [
-3300,
340
],
"parameters": {
"color": 5,
"width": 398,
"height": 642,
"content": "### Applicant Applied for Job in ERPNext\n\nYou need to go to Webhooks in ERPNext and Create a Webhook on Job Applicant Doc Type and trigger should be on insert.\n\nFirst do the Test Wehbook and Pin the Webhook.\n\nFollow the Tutorial"
},
"typeVersion": 1
},
{
"id": "4ed5dfbf-9b16-4f62-83e2-abb63421809b",
"name": "지원자 데이터",
"type": "n8n-nodes-base.set",
"position": [
-2640,
480
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "8d600a4f-14d3-4840-aea0-665d26e7771b",
"name": "body",
"type": "object",
"value": "={{ $json.body }}"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "4f141057-8dd6-429a-b48f-fd80b2666882",
"name": "ERPNext - 이력서 미첨부 시 거절",
"type": "n8n-nodes-base.erpNext",
"position": [
-2380,
800
],
"parameters": {
"docType": "Job%20Applicant",
"operation": "update",
"properties": {
"customProperty": [
{
"field": "status",
"value": "Rejected"
}
]
},
"documentName": "={{ $('ApplicantData').item.json.body.name }}"
},
"credentials": {
"erpNextApi": {
"id": "PInpnsxvPkvaiW0z",
"name": "ERPNext account"
}
},
"typeVersion": 1
},
{
"id": "de0a9900-4109-4092-ad3b-f36f02517fdf",
"name": "지원한 채용 공고",
"type": "n8n-nodes-base.if",
"position": [
-2140,
460
],
"parameters": {
"options": {
"ignoreCase": true
},
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": false,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "abbbd6f3-838e-43fb-a809-6bfffb153244",
"operator": {
"type": "string",
"operation": "notEquals"
},
"leftValue": "={{ $json.body.Job_opening }}",
"rightValue": "None"
}
]
}
},
"typeVersion": 2.2
},
{
"id": "1c8e889b-dcd9-4807-8528-a7f0300bf558",
"name": "ERPNext - 지원자 보류",
"type": "n8n-nodes-base.erpNext",
"position": [
-2180,
800
],
"parameters": {
"docType": "Job%20Applicant",
"operation": "update",
"properties": {
"customProperty": [
{
"field": "status",
"value": "Hold"
}
]
},
"documentName": "={{ $('ApplicantData').item.json.body.name }}"
},
"credentials": {
"erpNextApi": {
"id": "PInpnsxvPkvaiW0z",
"name": "ERPNext account"
}
},
"typeVersion": 1
},
{
"id": "548c61dd-bcc3-4a7f-970e-5ff734926499",
"name": "메모5",
"type": "n8n-nodes-base.stickyNote",
"position": [
-140,
343.6198532285906
],
"parameters": {
"color": 6,
"width": 258,
"height": 638.3801467714094,
"content": "### Get Job Opening Data\nFrom ERPNext\n\nAs Job is applied against a specific Job, you can now get the Job Opening Data which must be having the Job Description."
},
"typeVersion": 1
},
{
"id": "6266e3e0-9bd7-4ab6-a488-55f1b524000f",
"name": "채용 공고 가져오기",
"type": "n8n-nodes-base.erpNext",
"position": [
-80,
620
],
"parameters": {
"docType": "Job%20Opening",
"operation": "get",
"documentName": "={{ $('ApplicantData').item.json.body.Job_opening }}"
},
"credentials": {
"erpNextApi": {
"id": "PInpnsxvPkvaiW0z",
"name": "ERPNext account"
}
},
"typeVersion": 1
},
{
"id": "536755cf-19d6-44a4-8449-635f4562b61f",
"name": "메모7",
"type": "n8n-nodes-base.stickyNote",
"position": [
140,
320
],
"parameters": {
"color": 4,
"width": 406.7864870360547,
"height": 662,
"content": "### AI Agent to do its Job\nOpenAI\n\nSee full prompt which tells this AI Agent that you are a recruitment sepcialist and all the roles are defined in this node.\n\nIt will shortlist the candidate and will give the descriptive output with candidate fitlevel, score, rating and justification."
},
"typeVersion": 1
},
{
"id": "0072826c-0e24-4c1f-89f9-388dc6e59ae5",
"name": "메모8",
"type": "n8n-nodes-base.stickyNote",
"position": [
980,
320
],
"parameters": {
"color": 6,
"width": 438,
"height": 662,
"content": "### Update data in ERPNext\nHere First node will do the formatting of the data and will convert output from AI Agent to Appropriate Fields which are defined in ERPNext and then will Send to Next Node\n\n### ERPNext (HTTP Node)\nThis node will take the Data from Previouis Node and will update the Applicant Data in ERPNext"
},
"typeVersion": 1
},
{
"id": "28f23589-0608-4ed0-9e70-b6cbd31aa387",
"name": "Google Gemini 챗 모델",
"type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
"position": [
220,
800
],
"parameters": {
"options": {},
"modelName": "models/gemini-2.0-flash-exp"
},
"credentials": {
"googlePalmApi": {
"id": "pKFvSpPWSRFpnBoB",
"name": "Google Gemini(PaLM) Api account"
}
},
"typeVersion": 1
},
{
"id": "8bdd8f1c-e546-4ffb-a058-a3271fcad156",
"name": "필드로 변환",
"type": "n8n-nodes-base.code",
"position": [
660,
620
],
"parameters": {
"jsCode": "// Input text from the `output` field\nconst textOutput = $json.output || '';\n\n// Function to extract values from the text\nfunction extractFields(text) {\n const fields = {};\n\n // Regular expressions to extract each field\n const fitLevelMatch = text.match(/FitLevel:\\s*(.+)\\n/);\n const scoreMatch = text.match(/Score:\\s*(\\d+)\\n/);\n const ratingMatch = text.match(/Rating:\\s*(\\d+)\\n/);\n const justificationMatch = text.match(/Justification:\\s*([\\s\\S]+)/);\n\n // Assign extracted values to the fields\n fields.fit_level = fitLevelMatch ? fitLevelMatch[1].trim() : null;\n fields.score = scoreMatch ? scoreMatch[1].trim() : null;\n fields.applicant_rating = ratingMatch ? ratingMatch[1].trim() : null;\n fields.justification_by_ai = justificationMatch ? justificationMatch[1].trim() : null;\n\n return fields;\n}\n\n// Extract fields from the output\nconst extractedFields = extractFields(textOutput);\n\n// Return the fields as JSON\nreturn {\n json: extractedFields\n};\n"
},
"typeVersion": 2
},
{
"id": "ae1dc677-9ad7-4138-969f-2ee73b8537f9",
"name": "메모9",
"type": "n8n-nodes-base.stickyNote",
"position": [
1460,
320
],
"parameters": {
"color": 5,
"width": 226.43884349833064,
"height": 682,
"content": "### Selected or Rejected\n\nThe criteia for score is that if Score is 80 or above Candidate will be selected Else Rejected."
},
"typeVersion": 1
},
{
"id": "090f4f22-639a-4fc7-8351-04dafcc09638",
"name": "점수가 80 미만인 경우",
"type": "n8n-nodes-base.if",
"position": [
1520,
620
],
"parameters": {
"options": {},
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "loose"
},
"combinator": "and",
"conditions": [
{
"id": "5f845292-f4aa-44fb-a644-06c0736c3503",
"operator": {
"type": "number",
"operation": "lt"
},
"leftValue": "={{ $('Convert to Fields').item.json.score }}",
"rightValue": 80
}
]
},
"looseTypeValidation": true
},
"typeVersion": 2.2
},
{
"id": "0d7a84c2-0b1d-4e61-a3df-b81dd7981f1a",
"name": "지원자 거절",
"type": "n8n-nodes-base.httpRequest",
"position": [
1880,
460
],
"parameters": {
"url": "=https://erpnext.syncbricks.com/api/resource/Job Applicant/{{ $('ApplicantData').item.json.body.name }}",
"method": "PUT",
"options": {},
"jsonBody": "={\n \"status\": \"Rejected\"\n}",
"sendBody": true,
"sendHeaders": true,
"specifyBody": "json",
"authentication": "predefinedCredentialType",
"headerParameters": {
"parameters": [
{}
]
},
"nodeCredentialType": "erpNextApi"
},
"credentials": {
"erpNextApi": {
"id": "PInpnsxvPkvaiW0z",
"name": "ERPNext account"
}
},
"typeVersion": 4.2
},
{
"id": "a55e70d1-7070-407d-9107-41cb33d2f0ae",
"name": "지원자 데이터 업데이트",
"type": "n8n-nodes-base.httpRequest",
"position": [
1140,
620
],
"parameters": {
"url": "=https://erpnext.syncbricks.com/api/resource/Job Applicant/{{ $('ApplicantData').item.json.body.name }}",
"method": "PUT",
"options": {},
"jsonBody": "={\n \"applicant_rating\": \"{{ $json.applicant_rating }}\",\n \"custom_justification_by_ai\": \"{{ $json.justification_by_ai }}\",\n \"custom_fit_level\": \"{{ $json.fit_level }}\",\n \"custom_score\":\"{{ $json.score }}\"\n}\n\n\n\n\n",
"sendBody": true,
"sendHeaders": true,
"specifyBody": "json",
"authentication": "predefinedCredentialType",
"headerParameters": {
"parameters": [
{}
]
},
"nodeCredentialType": "erpNextApi"
},
"credentials": {
"erpNextApi": {
"id": "PInpnsxvPkvaiW0z",
"name": "ERPNext account"
}
},
"typeVersion": 4.2
},
{
"id": "044d26cb-2b34-4613-8d1d-20f40b47da29",
"name": "이력서 첨부 링크",
"type": "n8n-nodes-base.set",
"position": [
-1820,
560
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "7d0b8b98-0976-4c19-bc7c-738fabd60d28",
"name": "body.resume_attachment",
"type": "string",
"value": "={{ $json.body.resume_link }}"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "a17e9c94-0ec7-430f-adf3-109bcccf3bcb",
"name": "메모10",
"type": "n8n-nodes-base.stickyNote",
"position": [
-2874.102923130834,
680
],
"parameters": {
"color": 3,
"width": 875.658619343735,
"height": 302,
"content": "## Resume Available?\nFirst Node : If Resume is not attached or Then Job Applicant will be Rejected\nSecond Node : If job is not applied against opening then the Applicant will be kept on hold."
},
"typeVersion": 1
},
{
"id": "e2508130-4ecd-4d19-b41c-293006d17507",
"name": "이력서 링크 제공됨",
"type": "n8n-nodes-base.if",
"position": [
-2400,
480
],
"parameters": {
"options": {},
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "3cd3da7d-d0fb-43fd-be10-3c1e627846b9",
"operator": {
"type": "string",
"operation": "startsWith"
},
"leftValue": "={{ $json.body.resume_link }}",
"rightValue": "http"
}
]
}
},
"typeVersion": 2.2
},
{
"id": "e6770961-05b2-4488-99b1-7d1a219f8372",
"name": "지원자 수락",
"type": "n8n-nodes-base.httpRequest",
"position": [
1860,
760
],
"parameters": {
"url": "=https://erpnext.syncbricks.com/api/resource/Job Applicant/{{ $('ApplicantData').item.json.body.name }}",
"method": "PUT",
"options": {},
"jsonBody": "={\n \"status\": \"Accepted\"\n}",
"sendBody": true,
"sendHeaders": true,
"specifyBody": "json",
"authentication": "predefinedCredentialType",
"headerParameters": {
"parameters": [
{}
]
},
"nodeCredentialType": "erpNextApi"
},
"credentials": {
"erpNextApi": {
"id": "PInpnsxvPkvaiW0z",
"name": "ERPNext account"
}
},
"typeVersion": 4.2
},
{
"id": "6b7ad5c5-2a6f-4bb8-8296-3defb40f9605",
"name": "메모11",
"type": "n8n-nodes-base.stickyNote",
"position": [
-3800,
340
],
"parameters": {
"color": 4,
"width": 475.27306699862953,
"height": 636.1483291619771,
"content": "## Developed by Amjid Ali\n\nThank you for using this workflow template. It has taken me countless hours of hard work, research, and dedication to develop, and I sincerely hope it adds value to your work.\n\nIf you find this template helpful, I kindly ask you to consider supporting my efforts. Your support will help me continue improving and creating more valuable resources.\n\nYou can contribute via PayPal here:\n\nhttp://paypal.me/pmptraining\n\nFor Full Course about ERPNext or Automation using AI follow below link\n\nhttp://lms.syncbricks.com\n\nAdditionally, when sharing this template, I would greatly appreciate it if you include my original information to ensure proper credit is given.\n\nThank you for your generosity and support!\nEmail : amjid@amjidali.com\nhttps://linkedin.com/in/amjidali\nhttps://syncbricks.com\nhttps://youtube.com/@syncbricks"
},
"typeVersion": 1
},
{
"id": "173c6341-2ab7-4ee5-a6bd-0770ae19c013",
"name": "웹훅",
"type": "n8n-nodes-base.webhook",
"position": [
-3180,
620
],
"webhookId": "f003f8ea-1f24-457c-8f28-762bd7942023",
"parameters": {
"path": "syncbricks-com-tutorial-candidate-shortlist",
"options": {},
"httpMethod": "POST"
},
"typeVersion": 2
},
{
"id": "cb0a8dd4-6673-4043-af76-0bf4537a8173",
"name": "메모12",
"type": "n8n-nodes-base.stickyNote",
"position": [
-1980,
340
],
"parameters": {
"color": 6,
"width": 613.5767730410602,
"height": 654.6630436071407,
"content": "### Get file of Resume Detail from ERPNext Applicant\nExtract the Resume Download Link and Decide which Attachment type it is as every attachment will be treated differently.\nCurrently I provided only for PDF Version but you can add seperate flow for other versions"
},
"typeVersion": 1
},
{
"id": "101938bd-75cd-4557-a44f-ba64c4181f70",
"name": "메모13",
"type": "n8n-nodes-base.stickyNote",
"position": [
-2420,
340
],
"parameters": {
"color": 6,
"width": 429.96763122593137,
"height": 310.20584626167124,
"content": "### Validate if the Resume is Available and It is against a specific Job\nThese Nodes are to extract only the Required Data from the Webhook Node"
},
"typeVersion": 1
},
{
"id": "596bcbd5-b94a-4a06-aa83-f7d9dc6264be",
"name": "파일 형식",
"type": "n8n-nodes-base.switch",
"position": [
-1600,
560
],
"parameters": {
"rules": {
"values": [
{
"outputKey": "pdf",
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"operator": {
"type": "string",
"operation": "endsWith"
},
"leftValue": "={{ $json.body.resume_attachment }}",
"rightValue": ".pdf"
}
]
},
"renameOutput": true
},
{
"outputKey": "doc",
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "dabe1bd2-9aba-4a61-b0b3-08c22856b213",
"operator": {
"type": "string",
"operation": "contains"
},
"leftValue": "={{ $json.body.resume_attachment }}",
"rightValue": ".doc"
}
]
},
"renameOutput": true
},
{
"outputKey": ".jpg",
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "1101fc2e-4220-4795-9342-58d88ea146ce",
"operator": {
"type": "string",
"operation": "endsWith"
},
"leftValue": "={{ $json.body.resume_attachment }}",
"rightValue": ".jpg"
}
]
},
"renameOutput": true
}
]
},
"options": {}
},
"typeVersion": 3.2
},
{
"id": "cc7f4ca0-8e9b-49de-a7f1-f1f7913d6dcc",
"name": "PDF 이력서 다운로드",
"type": "n8n-nodes-base.httpRequest",
"position": [
-1160,
460
],
"parameters": {
"url": "={{ $json.body.resume_attachment }}",
"options": {}
},
"typeVersion": 4.2
},
{
"id": "1209643a-7133-45cf-98a3-e242e2e1766b",
"name": "PDF를 텍스트로 변환",
"type": "n8n-nodes-base.extractFromFile",
"position": [
-720,
440
],
"parameters": {
"options": {},
"operation": "pdf"
},
"typeVersion": 1
},
{
"id": "17430d0d-7bca-4ed9-b80e-d1f81dad5d58",
"name": "텍스트 파일을 텍스트로 변환 (예시)",
"type": "n8n-nodes-base.extractFromFile",
"position": [
-740,
680
],
"parameters": {
"options": {},
"operation": "text"
},
"typeVersion": 1
},
{
"id": "2ab3f083-66d7-4a28-9b00-b9dabcd84282",
"name": "병합1",
"type": "n8n-nodes-base.merge",
"position": [
-420,
620
],
"parameters": {},
"typeVersion": 3
},
{
"id": "e45d5828-1e7b-454e-9a79-7ab0f60e3cd9",
"name": "채용 AI 에이전트",
"type": "@n8n/n8n-nodes-langchain.agent",
"position": [
200,
620
],
"parameters": {
"text": "=System Prompt : \nYou are a highly skilled AI agent trained to compare and analyze text from resumes against job descriptions. Your primary goal is to assess whether the candidate is a good fit for the role based on the given inputs. You will receive two inputs:\n\n1. **Job Description**: A detailed description of the responsibilities, qualifications, and skills required for a specific job role.\n2. **Resume Text**: A summary of a candidate's qualifications, skills, experience, and education.\n\nYour task is to:\n1. **Analyze Match**: Compare the candidate's resume text against the job description and assess the alignment of:\n - Required skills\n - Relevant experience\n - Educational background\n - Certifications\n - Keywords mentioned in both texts (e.g., specific tools, methodologies, or terminologies).\n\n2. **Assess Fit**: Determine if the candidate is a strong, moderate, or weak fit for the role. Assign a score from 0 to 100 based on relevance:\n - **Strong Fit**: 80–100 (Candidate meets or exceeds the majority of the job requirements).\n - **Moderate Fit**: 50–79 (Candidate meets some key requirements but lacks in others).\n - **Weak Fit**: Below 50 (Candidate does not align with the role requirements).\n\n3. **Provide Justification**: Include a brief explanation of why the candidate is or isn’t a good fit, highlighting strengths, gaps, or missing criteria.\n\nOutput Format:\n- **Fit Level**: [Strong Fit / Moderate Fit / Weak Fit]\n- **Score**: [0–100]\n- **Rating**: [0–5]\n- **Justification**: A concise summary of the reasoning behind the fit level.\n\nRemember to maintain a neutral and objective tone in your analysis and ensure that your assessment is solely based on the information provided in the inputs.\"\n\n\nProvide me the output in the following format:\n\nFitLevel\n<fitLevel>\n\nScore:\n<score>\n\nRating:\n<rating>\n\nJustification:\n<justification>\n\nBelow are the inputs \n\nJob Title : {{ $json.job_title }}\nJob Desription : {{ $json.description }}\n\n\nHere here Job Applican't text from Resume : \n{{ $('PDF to Text').item.json.text }}\n",
"agent": "reActAgent",
"options": {},
"promptType": "define"
},
"typeVersion": 1.7
},
{
"id": "02d40fbc-3b2a-4350-bd01-2dcca11cf23b",
"name": "메모14",
"type": "n8n-nodes-base.stickyNote",
"position": [
560,
320
],
"parameters": {
"color": 6,
"width": 374.6910896370089,
"height": 662,
"content": "### Create Fields\n\nThis Java Script will convert the extracted fieldws from AI Agent and will create fields which are already created in ERPNext.\n\nEnsure to create below fields in ERPNext : \n\njustification_by_ai\nfit_level\nscore\n\napplicant_rating field is already there, which will be updated with 1 to 5 star"
},
"typeVersion": 1
},
{
"id": "fdc011c2-e734-44fe-8a83-975247445d16",
"name": "메모15",
"type": "n8n-nodes-base.stickyNote",
"position": [
1720,
320
],
"parameters": {
"color": 3,
"width": 394.2810709723076,
"height": 308.0357387860514,
"content": "### Update data in ERPNext\nAPI Call\nCandidate Rejected"
},
"typeVersion": 1
},
{
"id": "3c4174cc-b947-4461-87a6-a7dbd0e3c78d",
"name": "메모16",
"type": "n8n-nodes-base.stickyNote",
"position": [
1720,
660
],
"parameters": {
"color": 4,
"width": 385.4472695263088,
"height": 308.0357387860514,
"content": "### Update data in ERPNext\nAPI Call\nCandidate Rejected"
},
"typeVersion": 1
},
{
"id": "0116aa6d-2783-487b-b457-47a6b7d69f02",
"name": "Microsoft Outlook",
"type": "n8n-nodes-base.microsoftOutlook",
"position": [
2240,
460
],
"parameters": {
"additionalFields": {}
},
"credentials": {
"microsoftOutlookOAuth2Api": {
"id": "9gy3uvf3pmBdpEsq",
"name": "Microsoft Outlook Al Ansari"
}
},
"typeVersion": 2
},
{
"id": "f2eac576-3a17-46e8-8800-1ba250e53047",
"name": "메모17",
"type": "n8n-nodes-base.stickyNote",
"position": [
2140,
331.1661985540012
],
"parameters": {
"color": 6,
"width": 338.3336618143153,
"height": 623.107990360008,
"content": "### Notifiy Applicant either by Email or Whatsapp or SMS, Options are Limitless"
},
"typeVersion": 1
},
{
"id": "d4a6e756-923c-47c8-9c12-b1e8dcc873ca",
"name": "WhatsApp Business Cloud",
"type": "n8n-nodes-base.whatsApp",
"position": [
2280,
760
],
"parameters": {
"operation": "send",
"requestOptions": {},
"additionalFields": {}
},
"credentials": {
"whatsAppApi": {
"id": "E8IjegSMj5LTd8lA",
"name": "WhatsApp Syncbricks Access Token Never Expires"
}
},
"typeVersion": 1
}
],
"pinData": {},
"connections": {
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},
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]
]
}
}
}자주 묻는 질문
이 워크플로우를 어떻게 사용하나요?
위의 JSON 구성 코드를 복사하여 n8n 인스턴스에서 새 워크플로우를 생성하고 "JSON에서 가져오기"를 선택한 후, 구성을 붙여넣고 필요에 따라 인증 설정을 수정하세요.
이 워크플로우는 어떤 시나리오에 적합한가요?
고급 - 금융, 인공지능
유료인가요?
이 워크플로우는 완전히 무료이며 직접 가져와 사용할 수 있습니다. 다만, 워크플로우에서 사용하는 타사 서비스(예: OpenAI API)는 사용자 직접 비용을 지불해야 할 수 있습니다.
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저자
Amjid Ali
@amjid**Amjid Ali** is an automation expert and AI enthusiast specializing in creating intelligent workflows using low-code platforms like **n8n**. With a passion for simplifying complex processes, he designs solutions that enhance productivity and streamline operations. As an active contributor to the **n8n Creator Hub**, Amjid shares innovative use cases, practical templates, and best practices, empowering the community to unlock the full potential of workflow automation.
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