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实时自动化 LinkedIn 档案研究与 AI 外联(使用 Apify、Gemini 和 Sheets)

高级

这是一个Lead Generation, Multimodal AI领域的自动化工作流,包含 20 个节点。主要使用 If, Limit, GoogleSheets, Apify, ScheduleTrigger 等节点。 使用 Apify、Gemini 和 Sheets 自动化 LinkedIn 档案研究与邮件外联

前置要求
  • Google Sheets API 凭证
  • Google Gemini API Key
工作流预览
可视化展示节点连接关系,支持缩放和平移
导出工作流
复制以下 JSON 配置到 n8n 导入,即可使用此工作流
{
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    "instanceId": "1a54c41d9050a8f1fa6f74ca858828ad9fb97b9fafa3e9760e576171c531a787"
  },
  "name": "实时自动化 LinkedIn 档案研究与 AI 外联(使用 Apify、Gemini 和 Sheets)",
  "tags": [],
  "nodes": [
    {
      "id": "ecbfc577-7f4d-448c-8c70-4c6a80ba7629",
      "name": "获取表格中的行",
      "type": "n8n-nodes-base.googleSheets",
      "position": [
        -1792,
        336
      ],
      "parameters": {
        "options": {},
        "sheetName": {
          "__rl": true,
          "mode": "list",
          "value": 1023079571,
          "cachedResultUrl": "https://docs.google.com/spreadsheets/d/1nIGlVREvoz7iyCsOmCgqRXgKFFQZIVckV6a1KnDGpjM/edit#gid=1023079571",
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          "mode": "list",
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          "cachedResultUrl": "https://docs.google.com/spreadsheets/d/1nIGlVREvoz7iyCsOmCgqRXgKFFQZIVckV6a1KnDGpjM/edit?usp=drivesdk",
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        }
      },
      "typeVersion": 4.7
    },
    {
      "id": "efe97c07-f2d4-4f90-9f21-a503ebbd4103",
      "name": "限制",
      "type": "n8n-nodes-base.limit",
      "position": [
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      ],
      "parameters": {},
      "typeVersion": 1
    },
    {
      "id": "4f2e62e8-7e5e-434b-80f7-c2197ad1950c",
      "name": "获取数据集项",
      "type": "@apify/n8n-nodes-apify.apify",
      "position": [
        -944,
        320
      ],
      "parameters": {
        "offset": {},
        "resource": "Datasets",
        "datasetId": "={{ $json.defaultDatasetId }}"
      },
      "typeVersion": 1
    },
    {
      "id": "b8bdd09a-1e75-4a13-9fee-75ffc305fa67",
      "name": "追加或更新表格行",
      "type": "n8n-nodes-base.googleSheets",
      "position": [
        -672,
        320
      ],
      "parameters": {
        "columns": {
          "value": {
            "LinkedIn": "={{ $('Limit').item.json.LinkedIn }}",
            "Profile Data": "=About : {{ $json.basic_info.about }}\n\n{{ $json.experience.map((exp, i) => \n   \"Experience \" + (i+1) + \"\\n\" +\n   \"Title: \" + exp.title + \"\\n\" +\n   \"Company: \" + exp.company + \"\\n\" +\n   \"Location: \" + exp.location + \"\\n\" +\n   \"Description: \" + exp.description\n).join(\"\\n\\n\") }}\n\n"
          },
          "schema": [
            {
              "id": "First Name",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "First Name",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "Last Name",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "Last Name",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "Job Title",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "Job Title",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "Location",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "Location",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "LinkedIn",
              "type": "string",
              "display": true,
              "removed": false,
              "required": false,
              "displayName": "LinkedIn",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "Company Name",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "Company Name",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "Profile Data",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "Profile Data",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "Subject",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "Subject",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "Email Body",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "Email Body",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            }
          ],
          "mappingMode": "defineBelow",
          "matchingColumns": [
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          "attemptToConvertTypes": false,
          "convertFieldsToString": false
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          "value": 1023079571,
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      "type": "n8n-nodes-base.googleSheets",
      "position": [
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      ],
      "parameters": {
        "options": {},
        "sheetName": {
          "__rl": true,
          "mode": "list",
          "value": 1023079571,
          "cachedResultUrl": "https://docs.google.com/spreadsheets/d/1nIGlVREvoz7iyCsOmCgqRXgKFFQZIVckV6a1KnDGpjM/edit#gid=1023079571",
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          "__rl": true,
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    {
      "id": "0ca835dc-bc3f-49bf-85d8-08a8d41d3502",
      "name": "结构化输出解析器",
      "type": "@n8n/n8n-nodes-langchain.outputParserStructured",
      "position": [
        240,
        512
      ],
      "parameters": {
        "jsonSchemaExample": "{\n  \"subject\": \"A short, catchy, question-based subject line\",\n  \"email_body\": \"The full email body, 100-120 words, without any salutation or sign-off.\"\n}"
      },
      "typeVersion": 1.3
    },
    {
      "id": "d1412a37-4f94-4efa-aac8-ba7f129b2bb7",
      "name": "Google Gemini聊天模型",
      "type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
      "position": [
        64,
        512
      ],
      "parameters": {
        "options": {}
      },
      "typeVersion": 1
    },
    {
      "id": "6e9c4aac-17fc-4b21-a832-038b6571a52e",
      "name": "计划触发器",
      "type": "n8n-nodes-base.scheduleTrigger",
      "position": [
        -2000,
        336
      ],
      "parameters": {
        "rule": {
          "interval": [
            {
              "field": "minutes",
              "minutesInterval": 2
            }
          ]
        }
      },
      "typeVersion": 1.2
    },
    {
      "id": "27f7cb9e-f89a-4496-b2ff-0cd8fb0cf6af",
      "name": "便签",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -2048,
        80
      ],
      "parameters": {
        "color": 2,
        "width": 384,
        "height": 416,
        "content": "## ⏰ 计划触发器 & 📄 Google Sheets (输入)"
      },
      "typeVersion": 1
    },
    {
      "id": "20b443fd-25df-4397-b167-cfa1ae1616fc",
      "name": "便签 1",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -1616,
        80
      ],
      "parameters": {
        "color": 6,
        "width": 384,
        "height": 416,
        "content": "## 🔍 If 检查 & ⚖️ 限制"
      },
      "typeVersion": 1
    },
    {
      "id": "fd519317-971a-4cbf-a891-dcb61965c30f",
      "name": "便签 2",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -1200,
        80
      ],
      "parameters": {
        "color": 4,
        "width": 384,
        "height": 416,
        "content": "## 🤖 Apify Actor & 📂 数据集"
      },
      "typeVersion": 1
    },
    {
      "id": "5b2af68b-9acb-4021-9211-ea9f947cffbf",
      "name": "便签 3",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -768,
        64
      ],
      "parameters": {
        "color": 5,
        "width": 288,
        "height": 432,
        "content": "## 💾 Google Sheets (个人资料数据)"
      },
      "typeVersion": 1
    },
    {
      "id": "5fbf3fc9-7a32-46b3-92a1-95758b9a1337",
      "name": "便签 4",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -432,
        80
      ],
      "parameters": {
        "color": 3,
        "width": 368,
        "height": 384,
        "content": "## 📄 再次获取行 & 🔍 If 检查 (邮件)"
      },
      "typeVersion": 1
    },
    {
      "id": "6b63c91d-a436-4c1d-8d1c-3e5b3f84194e",
      "name": "便签 5",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        0,
        0
      ],
      "parameters": {
        "width": 368,
        "height": 464,
        "content": "## 🧠 LLM Chain (通过 LangChain 使用 Gemini)"
      },
      "typeVersion": 1
    },
    {
      "id": "36ffcba7-23b8-45fc-b7dd-612f8537c293",
      "name": "便签6",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        416,
        80
      ],
      "parameters": {
        "color": 5,
        "width": 320,
        "height": 384,
        "content": "## 💾 Google Sheets (最终邮件)"
      },
      "typeVersion": 1
    },
    {
      "id": "6bcd2902-cf7c-4235-ad92-d8ea28392af4",
      "name": "检查没有数据的个人资料",
      "type": "n8n-nodes-base.if",
      "position": [
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      ],
      "parameters": {
        "options": {},
        "conditions": {
          "options": {
            "version": 2,
            "leftValue": "",
            "caseSensitive": true,
            "typeValidation": "strict"
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              "operator": {
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                "operation": "empty",
                "singleValue": true
              },
              "leftValue": "={{ $json[\"Profile Data\"] }}",
              "rightValue": ""
            },
            {
              "id": "5b0584d8-cfe8-4758-b097-cb0ecd87f5e4",
              "operator": {
                "type": "string",
                "operation": "empty",
                "singleValue": true
              },
              "leftValue": "={{ $json.Subject }}",
              "rightValue": ""
            }
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        }
      },
      "typeVersion": 2.2
    },
    {
      "id": "77f3dbf8-9218-44cf-a03f-feacfa4a1906",
      "name": "运行个人资料提取 Actor",
      "type": "@apify/n8n-nodes-apify.apify",
      "position": [
        -1152,
        320
      ],
      "parameters": {
        "actorId": {
          "__rl": true,
          "mode": "list",
          "value": "VhxlqQXRwhW8H5hNV",
          "cachedResultUrl": "https://console.apify.com/actors/VhxlqQXRwhW8H5hNV/input",
          "cachedResultName": "Linkedin Profile Details Scraper + EMAIL (No Cookies Required) (apimaestro/linkedin-profile-detail)"
        },
        "timeout": {},
        "customBody": "={\n    \"includeEmail\": false,\n    \"username\": \"{{ $json.LinkedIn }}\"\n}"
      },
      "typeVersion": 1
    },
    {
      "id": "02725c27-8264-4b8d-a725-18947a0c8b6b",
      "name": "检查没有邮件草稿的个人资料",
      "type": "n8n-nodes-base.if",
      "position": [
        -208,
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      ],
      "parameters": {
        "options": {},
        "conditions": {
          "options": {
            "version": 2,
            "leftValue": "",
            "caseSensitive": true,
            "typeValidation": "strict"
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          "combinator": "and",
          "conditions": [
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              "id": "dcf02764-abdc-4eca-8022-b0c585301927",
              "operator": {
                "type": "string",
                "operation": "notEmpty",
                "singleValue": true
              },
              "leftValue": "={{ $json[\"Profile Data\"] }}",
              "rightValue": ""
            },
            {
              "id": "87fc4d1b-97e7-4fcd-af85-f1414d476b67",
              "operator": {
                "type": "string",
                "operation": "empty",
                "singleValue": true
              },
              "leftValue": "={{ $json.Subject }}",
              "rightValue": ""
            },
            {
              "id": "4a7ddabd-14bd-429f-97e3-513abf6c62f8",
              "operator": {
                "type": "string",
                "operation": "empty",
                "singleValue": true
              },
              "leftValue": "={{ $json[\"Email Body\"] }}",
              "rightValue": ""
            }
          ]
        }
      },
      "typeVersion": 2.2
    },
    {
      "id": "f81e7880-4ae7-4f32-864a-05bb176a9e58",
      "name": "超个性化邮件生成器",
      "type": "@n8n/n8n-nodes-langchain.chainLlm",
      "position": [
        80,
        304
      ],
      "parameters": {
        "text": "=**Act as an expert B2B cold email copywriter.** Your specialty is writing highly personalized, concise, and compelling emails that get replies from busy executives. Your style is peer-to-peer, respectful, and avoids generic sales jargon.\n\n\n\n**Your Goal:** Generate 1 distinct email draft to a prospect based on their professional profile. Each email must feel like I have personally researched them and understood their career journey.\n\n\n\n**My Context:**\n\n\n*   **My Company/Service:** We offer MLOps solutions that help companies significantly reduce their cloud costs for AI and machine learning workloads without sacrificing performance.\n\n\n*   **My Core Value Proposition:** We help tech leaders ship AI features faster and more profitably by optimizing their infrastructure.\n\n\n*   **My Call to Action (CTA):** An offer for a complimentary, no-obligation audit of their current ML infrastructure to identify immediate cost-saving opportunities.\n\n\n\n**Prospect's Profile:**\n\n\nFULL PROFILE DETAILS HERE \nFirst Name: {{ $json['First Name'] }}\nLast Name: {{ $json['Last Name'] }}\nJob Title: {{ $json['Job Title'] }}\nCompany Name: {{ $json['Company Name'] }}\nProfile Data: {{ $json['Profile Data'] }}\n\n**Instructions for Crafting the Emails:**\n\n\n\n1.  **Scrutinize the Profile:** Read the entire profile provided. Do not just look at the current job title. Instead, identify the most unique and compelling \"nuggets\" of information. Look for:\n\n\n    *   **Unusual Career Paths:** (e.g., from SysAdmin to VP of Product, or Trader to COO).\n\n\n    *   **Long Tenure / Promotions:** (e.g., spending 9+ years at one company and rising through the ranks).\n\n\n    *   **Specific, Quantifiable Achievements:** (e.g., \"scaled to 4M members\").\n\n\n    *   **\"Boomerang\" Employment:** (e.g., leaving a company and returning later in a more senior role).\n\n\n    *   **Consistent Themes:** (e.g., a career-long focus on \"health and wealth outcomes\").\n\n\n    *   **Past Roles at well-known companies** that are relevant to their current role.\n\n\n\n2.  **Create a \"Hook\" from a Nugget:** Start each email with a genuine, specific observation based on one of these nuggets. This is the most critical step.\n\n\n    *   **Good Example:** \"Your 9-year journey at Wanderu, from Director to leading both Product & Technology, is incredibly impressive.\"\n\n\n    *   **Bad Example:** \"I saw on your LinkedIn profile that you are the VP at Wanderu.\"\n\n\n\n3.  **Build a \"Bridge\":** Immediately connect your observation (the Hook) to a relevant business problem that the prospect likely faces in their *current* role. The problem should be tailored to their title:\n\n\n    *   **For a CTO/VP Engineering:** Frame the problem around infrastructure complexity, scalability, and technical debt.\n\n\n    *   **For a COO/GM:** Frame the problem around operational efficiency, P&L, gross margins, and profitability (COGS).\n\n\n    *   **For a VP Product:** Frame the problem around speed-to-market, feature ROI, and the budget for new initiatives.\n\n\n\n4.  **Introduce the Solution:** Seamlessly introduce my service (MLOps for cost reduction) as the direct solution to the problem you just framed. Use my Core Value Proposition here.\n\n\n\n5.  **Deliver the Call to Action:** End with the specific, low-friction CTA I provided.\n\n\n\n**Final Output Requirements:**\n\n\n*   Provide 1 distinct drafts, each using a different \"nugget\" or angle for the hook.\n\n\n*   Keep each email under 150 words.\n\n\n*   Use a confident, peer-level tone. Avoid overly formal or submissive language.\n\n\n*   Create a compelling, short subject line for each draft.\n\nCritical Information:\n- The output should be divided into \nsubject: \"Subject line\"\nBody: \"Content for email\"\n- Each mail should be different to other one.",
        "batching": {},
        "promptType": "define",
        "hasOutputParser": true
      },
      "typeVersion": 1.7
    },
    {
      "id": "556499f4-f086-45bf-aad7-90e78c4dfc5b",
      "name": "最终输出",
      "type": "n8n-nodes-base.googleSheets",
      "position": [
        512,
        304
      ],
      "parameters": {
        "columns": {
          "value": {
            "Subject": "={{ $json.output.subject }}",
            "LinkedIn": "={{ $('Check Profiles with No Email Drafts').item.json.LinkedIn }}",
            "Email Body": "={{ $json.output.email_body }}"
          },
          "schema": [
            {
              "id": "First Name",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "First Name",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "Last Name",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "Last Name",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "Job Title",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "Job Title",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "Location",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "Location",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "LinkedIn",
              "type": "string",
              "display": true,
              "removed": false,
              "required": false,
              "displayName": "LinkedIn",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "Company Name",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "Company Name",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "Profile Data",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "Profile Data",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "Subject",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "Subject",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "Email Body",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "Email Body",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            }
          ],
          "mappingMode": "defineBelow",
          "matchingColumns": [
            "LinkedIn"
          ],
          "attemptToConvertTypes": false,
          "convertFieldsToString": false
        },
        "options": {},
        "operation": "appendOrUpdate",
        "sheetName": {
          "__rl": true,
          "mode": "list",
          "value": 1023079571,
          "cachedResultUrl": "https://docs.google.com/spreadsheets/d/1nIGlVREvoz7iyCsOmCgqRXgKFFQZIVckV6a1KnDGpjM/edit#gid=1023079571",
          "cachedResultName": "Sheet10"
        },
        "documentId": {
          "__rl": true,
          "mode": "list",
          "value": "1nIGlVREvoz7iyCsOmCgqRXgKFFQZIVckV6a1KnDGpjM",
          "cachedResultUrl": "https://docs.google.com/spreadsheets/d/1nIGlVREvoz7iyCsOmCgqRXgKFFQZIVckV6a1KnDGpjM/edit?usp=drivesdk",
          "cachedResultName": "MLOps CXOs Bay Area"
        }
      },
      "typeVersion": 4.7
    }
  ],
  "active": false,
  "pinData": {},
  "settings": {
    "executionOrder": "v1"
  },
  "versionId": "2d96068c-2cd4-48c7-adb3-f5139666adc1",
  "connections": {
    "Limit": {
      "main": [
        [
          {
            "node": "Runs Profile Extraction Actor",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Schedule Trigger": {
      "main": [
        [
          {
            "node": "Get row(s) in sheet",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Get dataset items": {
      "main": [
        [
          {
            "node": "Append or update row in sheet",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Get row(s) in sheet": {
      "main": [
        [
          {
            "node": "Check Profiles with no Data",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Get row(s) in sheet1": {
      "main": [
        [
          {
            "node": "Check Profiles with No Email Drafts",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Google Gemini Chat Model": {
      "ai_languageModel": [
        [
          {
            "node": "Hyper Personalised Email Generator",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    },
    "Structured Output Parser": {
      "ai_outputParser": [
        [
          {
            "node": "Hyper Personalised Email Generator",
            "type": "ai_outputParser",
            "index": 0
          }
        ]
      ]
    },
    "Check Profiles with no Data": {
      "main": [
        [
          {
            "node": "Limit",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Append or update row in sheet": {
      "main": [
        [
          {
            "node": "Get row(s) in sheet1",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Runs Profile Extraction Actor": {
      "main": [
        [
          {
            "node": "Get dataset items",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Hyper Personalised Email Generator": {
      "main": [
        [
          {
            "node": "Final Output",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Check Profiles with No Email Drafts": {
      "main": [
        [
          {
            "node": "Hyper Personalised Email Generator",
            "type": "main",
            "index": 0
          }
        ]
      ]
    }
  }
}
常见问题

如何使用这个工作流?

复制上方的 JSON 配置代码,在您的 n8n 实例中创建新工作流并选择「从 JSON 导入」,粘贴配置后根据需要修改凭证设置即可。

这个工作流适合什么场景?

高级 - 潜在客户开发, 多模态 AI

需要付费吗?

本工作流完全免费,您可以直接导入使用。但请注意,工作流中使用的第三方服务(如 OpenAI API)可能需要您自行付费。

工作流信息
难度等级
高级
节点数量20
分类2
节点类型9
难度说明

适合高级用户,包含 16+ 个节点的复杂工作流

作者
Intuz

Intuz

@intuz

Workflow automation can help automate your routine activities and help saves $$$, as well as hours of time. As a boutique tech consulting company, Intuz help businesses with custom AI/ML, AI Workflow Automations, and software development. Automate your business workflow for: Sales Marketing Accounting Finance Operations E-Commerce Customer Support Admin & Backoffice Logistics & Supply Chain

外部链接
在 n8n.io 查看

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