Cybernative Technologies This workflow corresponds to n8n.io template #16223 — we link there as the canonical source.
This workflow follows the Agent → Google Sheets recipe pattern — see all workflows that pair these two integrations.
The workflow JSON
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{
"id": "CEyPK3FFnZ8Y66GV",
"meta": {
"templateCredsSetupCompleted": true
},
"name": "AI Company Data Enrichment Pipeline",
"tags": [],
"nodes": [
{
"id": "69da91e3-bcf5-4619-b6e3-d9724284f905",
"name": "\ud83d\udccb Setup Instructions",
"type": "n8n-nodes-base.stickyNote",
"position": [
-192,
208
],
"parameters": {
"color": 5,
"width": 420,
"height": 588,
"content": "## \ud83c\udfd7\ufe0f SETUP REQUIRED\n\n**Before running this workflow:**\n\n1. **Source Sheet**: Connect your Google Sheets credential and set the `Get Companies` node to point to your input spreadsheet.\n - Required columns: `Company Name`, `Website`, `Enriched`\n - Leave `Enriched` blank for new rows\n\n2. **Output Sheet**: Set the `Append Enriched Row` node to your destination spreadsheet.\n - Required columns: `Company Name`, `Website`, `Industry`, `Description`, `Target Customers`, `Headquarters`, `Estimated Size`\n\n3. **AI Model**: Connect your Google Gemini API credential in the `Gemini Flash` node.\n\n4. **Search Tool**: Connect your SerpAPI credential in the `Web Search (SerpAPI)` node.\n\n5. **Mark as Done**: Set this node to your source spreadsheet (same as step 1) to update the `Enriched` column to `Yes`.\n\n---\n\ud83d\udca1 *Tip: Duplicate your source sheet before first run.*"
},
"typeVersion": 1
},
{
"id": "04fd3c13-9559-42ee-913d-85cf6459346b",
"name": "\ud83d\udccb Section: Read & Filter",
"type": "n8n-nodes-base.stickyNote",
"position": [
304,
368
],
"parameters": {
"color": 7,
"width": 520,
"height": 196,
"content": "## \u2460 READ & FILTER\n\nReads all companies from your source Google Sheet, extracts only the relevant fields (`Company Name`, `Website`, `Enriched`), then skips any row already marked `Enriched = Yes`.\n\n**Customise:** Change the sheet/tab in `Read Source Sheet`."
},
"typeVersion": 1
},
{
"id": "1f4cf9ae-8bbc-4f7b-b305-873a0a705e65",
"name": "\ud83d\udccb Section: AI Enrichment",
"type": "n8n-nodes-base.stickyNote",
"position": [
1008,
320
],
"parameters": {
"color": 6,
"width": 520,
"height": 252,
"content": "## \u2461 AI ENRICHMENT\n\nFor each unenriched company, the AI Agent:\n- Searches the web via SerpAPI\n- Extracts: industry, description, target customers, HQ, and estimated size\n- Returns structured JSON via the Output Parser\n\n**Customise:** Swap `Gemini Flash` for any LangChain-compatible model (OpenAI, Claude, etc.)."
},
"typeVersion": 1
},
{
"id": "a1e14b76-848e-4a34-a209-a19d6bf236fe",
"name": "\ud83d\udccb Section: Write Output",
"type": "n8n-nodes-base.stickyNote",
"position": [
1568,
368
],
"parameters": {
"color": 4,
"width": 520,
"height": 184,
"content": "## \u2462 WRITE OUTPUT\n\nCleans the enriched data (converts the `target_customers` array to a comma-separated string), appends a new row to the output sheet, then marks the source row as `Enriched = Yes` to prevent duplicate processing.\n\n**Customise:** Add or remove columns in `Append Enriched Row`."
},
"typeVersion": 1
},
{
"id": "b9585aca-aebd-4284-ad1a-d9e5d364bd52",
"name": "\u25b6 Run Enrichment",
"type": "n8n-nodes-base.manualTrigger",
"position": [
304,
608
],
"parameters": {},
"typeVersion": 1
},
{
"id": "47fd03d7-936d-4583-bbca-ad486e89bf7f",
"name": "Read Source Sheet",
"type": "n8n-nodes-base.googleSheets",
"position": [
512,
608
],
"parameters": {
"options": {},
"sheetName": {
"__rl": true,
"mode": "name",
"value": "Sheet1"
},
"documentId": {
"__rl": true,
"mode": "id",
"value": "YOUR_SOURCE_SHEET_ID"
}
},
"typeVersion": 4.5
},
{
"id": "8235c4cf-ba6a-45e5-b7b6-022152c634fe",
"name": "Extract Relevant Fields",
"type": "n8n-nodes-base.set",
"position": [
736,
608
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "field-company-name",
"name": "Company Name",
"type": "string",
"value": "={{ $json[\"Company Name\"] }}"
},
{
"id": "field-website",
"name": "Website",
"type": "string",
"value": "={{ $json.Website }}"
},
{
"id": "field-enriched",
"name": "Enriched",
"type": "string",
"value": "={{ $json.Enriched }}"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "c331d771-b80a-4c41-bda7-c7754ddd1869",
"name": "Skip Already Enriched",
"type": "n8n-nodes-base.if",
"position": [
912,
608
],
"parameters": {
"options": {},
"conditions": {
"options": {
"version": 3,
"leftValue": "",
"caseSensitive": false,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "check-not-enriched",
"operator": {
"type": "string",
"operation": "notEquals"
},
"leftValue": "={{ $json.Enriched }}",
"rightValue": "Yes"
}
]
}
},
"typeVersion": 2.3
},
{
"id": "5c45a5f6-803f-485e-aba3-c1b032b999a6",
"name": "AI Enrichment Agent",
"type": "@n8n/n8n-nodes-langchain.agent",
"maxTries": 3,
"position": [
1152,
592
],
"parameters": {
"text": "=Company Name: {{ $json[\"Company Name\"] }}\nWebsite URL: {{ $json.Website }}",
"options": {
"systemMessage": "You are a company data enrichment engine.\n\nYour task is to research the provided company using its name and website, then return ONLY valid JSON matching the required schema.\n\nRules:\n1. Return ONLY JSON \u2014 no markdown, no explanations, no extra text.\n2. Use exact field names from the schema.\n3. If a value cannot be determined with confidence, return an empty string (\"\").\n4. Keep descriptions under 20 words.\n5. target_customers must always be an array of strings.\n6. headquarters must be formatted as: \"City, Country\".\n7. estimated_size must be exactly one of: Startup | Small | Medium | Large | Enterprise\n8. industry must be exactly one of: AI | Software | Cybersecurity | FinTech | HealthTech | EdTech | E-commerce | Marketing | Manufacturing | Consulting | Logistics | Telecommunications | Media | Real Estate | Energy | Biotechnology | Finance | Healthcare | Retail | Other\n9. target_customers must only contain values from: Businesses | Enterprises | Startups | Developers | Researchers | Consumers | Government | Educational Institutions | Healthcare Providers | Financial Institutions | Nonprofits | Tech Companies | Small Businesses\n10. Always populate company_name and website from the input exactly as given.\n11. Never invent or hallucinate data. Research first, then respond."
},
"promptType": "define",
"hasOutputParser": true
},
"retryOnFail": true,
"typeVersion": 3,
"waitBetweenTries": 2000
},
{
"id": "95e8f953-5229-4ae3-ad60-8904a0fb1891",
"name": "Structured Output Parser",
"type": "@n8n/n8n-nodes-langchain.outputParserStructured",
"position": [
1392,
832
],
"parameters": {
"jsonSchemaExample": "{\n \"company_name\": \"OpenAI\",\n \"website\": \"openai.com\",\n \"industry\": \"AI\",\n \"description\": \"Develops AI models and products for businesses and consumers\",\n \"target_customers\": [\n \"Businesses\",\n \"Developers\"\n ],\n \"headquarters\": \"San Francisco, United States\",\n \"estimated_size\": \"Large\"\n}"
},
"typeVersion": 1.3
},
{
"id": "bdb816a4-d9e2-4ad1-ba66-270b10d6c71e",
"name": "Web Search (SerpAPI)",
"type": "@n8n/n8n-nodes-langchain.toolSerpApi",
"position": [
1216,
832
],
"parameters": {
"options": {}
},
"typeVersion": 1
},
{
"id": "5c6c2bc6-1013-4951-8062-1347ff613a49",
"name": "Gemini Flash",
"type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
"position": [
1056,
832
],
"parameters": {
"options": {},
"modelName": "models/gemini-2.0-flash"
},
"typeVersion": 1
},
{
"id": "e3ad40be-8f07-441b-889a-812ff53ecaa8",
"name": "Normalize Output Data",
"type": "n8n-nodes-base.code",
"position": [
1472,
592
],
"parameters": {
"mode": "runOnceForEachItem",
"jsCode": "// Safely join target_customers array to a comma-separated string\nconst output = $json.output || {};\nconst targets = Array.isArray(output.target_customers)\n ? output.target_customers.join(\", \")\n : (output.target_customers || \"\");\n\nreturn {\n company_name: output.company_name || \"\",\n website: output.website || \"\",\n industry: output.industry || \"\",\n description: output.description || \"\",\n target_customers: targets,\n headquarters: output.headquarters || output.headquaters || \"\",\n estimated_size: output.estimated_size || \"\"\n};\n"
},
"typeVersion": 2
},
{
"id": "999f2a2a-9459-477a-9797-d760c258406e",
"name": "Append Enriched Row",
"type": "n8n-nodes-base.googleSheets",
"position": [
1664,
592
],
"parameters": {
"columns": {
"value": {
"Website": "={{ $json.website }}",
"Industry": "={{ $json.industry }}",
"Description": "={{ $json.description }}",
"Company Name": "={{ $json.company_name }}",
"Headquarters": "={{ $json.headquarters }}",
"Estimated Size": "={{ $json.estimated_size }}",
"Target Customers": "={{ $json.target_customers }}"
},
"schema": [
{
"id": "Company Name",
"type": "string",
"display": true,
"required": false,
"displayName": "Company Name",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Website",
"type": "string",
"display": true,
"required": false,
"displayName": "Website",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Industry",
"type": "string",
"display": true,
"required": false,
"displayName": "Industry",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Description",
"type": "string",
"display": true,
"required": false,
"displayName": "Description",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Target Customers",
"type": "string",
"display": true,
"required": false,
"displayName": "Target Customers",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Headquarters",
"type": "string",
"display": true,
"required": false,
"displayName": "Headquarters",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Estimated Size",
"type": "string",
"display": true,
"required": false,
"displayName": "Estimated Size",
"defaultMatch": false,
"canBeUsedToMatch": true
}
],
"mappingMode": "defineBelow",
"matchingColumns": [
"Company Name"
],
"attemptToConvertTypes": false,
"convertFieldsToString": false
},
"options": {},
"operation": "append",
"sheetName": {
"__rl": true,
"mode": "name",
"value": "Enriched"
},
"documentId": {
"__rl": true,
"mode": "id",
"value": "YOUR_OUTPUT_SHEET_ID"
}
},
"typeVersion": 4.5
},
{
"id": "56044593-f73d-4e87-86c3-9b2291e4baf3",
"name": "Mark as Enriched",
"type": "n8n-nodes-base.googleSheets",
"position": [
1856,
592
],
"parameters": {
"columns": {
"value": {
"Enriched": "Yes",
"Company Name": "={{ $json.company_name }}"
},
"schema": [
{
"id": "Company Name",
"type": "string",
"display": true,
"required": false,
"displayName": "Company Name",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Enriched",
"type": "string",
"display": true,
"required": false,
"displayName": "Enriched",
"defaultMatch": false,
"canBeUsedToMatch": true
}
],
"mappingMode": "defineBelow",
"matchingColumns": [
"Company Name"
],
"attemptToConvertTypes": false,
"convertFieldsToString": false
},
"options": {},
"operation": "update",
"sheetName": {
"__rl": true,
"mode": "name",
"value": "Sheet1"
},
"documentId": {
"__rl": true,
"mode": "id",
"value": "YOUR_SOURCE_SHEET_ID"
}
},
"typeVersion": 4.5
}
],
"active": false,
"settings": {
"executionOrder": "v1"
},
"versionId": "19fd4c5c-fc60-45b1-9a5b-6c3971453e99",
"connections": {
"Gemini Flash": {
"ai_languageModel": [
[
{
"node": "AI Enrichment Agent",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Read Source Sheet": {
"main": [
[
{
"node": "Extract Relevant Fields",
"type": "main",
"index": 0
}
]
]
},
"\u25b6 Run Enrichment": {
"main": [
[
{
"node": "Read Source Sheet",
"type": "main",
"index": 0
}
]
]
},
"AI Enrichment Agent": {
"main": [
[
{
"node": "Normalize Output Data",
"type": "main",
"index": 0
}
]
]
},
"Append Enriched Row": {
"main": [
[
{
"node": "Mark as Enriched",
"type": "main",
"index": 0
}
]
]
},
"Web Search (SerpAPI)": {
"ai_tool": [
[
{
"node": "AI Enrichment Agent",
"type": "ai_tool",
"index": 0
}
]
]
},
"Normalize Output Data": {
"main": [
[
{
"node": "Append Enriched Row",
"type": "main",
"index": 0
}
]
]
},
"Skip Already Enriched": {
"main": [
[
{
"node": "AI Enrichment Agent",
"type": "main",
"index": 0
}
]
]
},
"Extract Relevant Fields": {
"main": [
[
{
"node": "Skip Already Enriched",
"type": "main",
"index": 0
}
]
]
},
"Structured Output Parser": {
"ai_outputParser": [
[
{
"node": "AI Enrichment Agent",
"type": "ai_outputParser",
"index": 0
}
]
]
}
}
}
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About this workflow
This workflow manually runs a company enrichment pipeline that reads companies from Google Sheets, uses SerpAPI web search plus Google Gemini to generate structured company details, writes the enriched data to a second Google Sheet, and marks the source rows as enriched to avoid…
Source: https://n8n.io/workflows/16223/ — original creator credit. Request a take-down →
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