The workflow JSON
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{
"name": "Prospec\u00e7\u00e3o Ativa - Financial Services & M\u00eddia LATAM",
"nodes": [
{
"parameters": {
"rule": {
"interval": [
{}
]
}
},
"type": "n8n-nodes-base.scheduleTrigger",
"typeVersion": 1.2,
"position": [
-1600,
0
],
"id": "trigger-001",
"name": "Manual Trigger"
},
{
"parameters": {
"method": "POST",
"url": "https://api.apollo.io/v1/mixed_companies/search",
"sendHeaders": true,
"headerParameters": {
"parameters": [
{
"name": "Content-Type",
"value": "application/json"
},
{
"name": "X-Api-Key",
"value": "SUA_APOLLO_API_KEY"
}
]
},
"sendBody": true,
"specifyBody": "json",
"jsonBody": "={\n \"page\": 1,\n \"per_page\": 100,\n \"organization_industry_tag_ids\": [],\n \"organization_locations\": [\n \"Brazil\",\n \"Mexico\",\n \"Colombia\",\n \"Argentina\",\n \"Chile\",\n \"Peru\",\n \"Ecuador\",\n \"Venezuela\",\n \"Bolivia\",\n \"Paraguay\",\n \"Uruguay\"\n ],\n \"q_organization_keyword_tags\": [\n \"financial services\",\n \"fintech\",\n \"banking\",\n \"media\",\n \"journalism\",\n \"broadcasting\"\n ],\n \"organization_num_employees_ranges\": [\n \"50,500\"\n ]\n}",
"options": {}
},
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 4.3,
"position": [
-1360,
0
],
"id": "apollo-001",
"name": "Apollo - Buscar Empresas"
},
{
"parameters": {
"fieldToSplitOut": "organizations",
"options": {}
},
"type": "n8n-nodes-base.splitOut",
"typeVersion": 1,
"position": [
-1120,
0
],
"id": "split-001",
"name": "Split Empresas"
},
{
"parameters": {
"options": {}
},
"type": "n8n-nodes-base.splitInBatches",
"typeVersion": 3,
"position": [
-880,
0
],
"id": "loop-001",
"name": "Loop Over Empresas"
},
{
"parameters": {
"method": "POST",
"url": "https://api.tavily.com/search",
"sendHeaders": true,
"headerParameters": {
"parameters": [
{
"name": "Content-Type",
"value": "application/json"
}
]
},
"sendBody": true,
"specifyBody": "json",
"jsonBody": "={\n \"api_key\": \"SUA_TAVILY_API_KEY\",\n \"query\": \"{{ $json.name }} merger acquisition acquired M&A Latin America\",\n \"search_depth\": \"basic\",\n \"max_results\": 3\n}",
"options": {}
},
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 4.3,
"position": [
-640,
-160
],
"id": "tavily-ma",
"name": "Tavily - Check M&A"
},
{
"parameters": {
"method": "POST",
"url": "https://api.tavily.com/search",
"sendHeaders": true,
"headerParameters": {
"parameters": [
{
"name": "Content-Type",
"value": "application/json"
}
]
},
"sendBody": true,
"specifyBody": "json",
"jsonBody": "={\n \"api_key\": \"SUA_TAVILY_API_KEY\",\n \"query\": \"{{ $('Loop Over Empresas').item.json.name }} scandal fraud corruption lawsuit investigation\",\n \"search_depth\": \"basic\",\n \"max_results\": 3\n}",
"options": {}
},
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 4.3,
"position": [
-640,
0
],
"id": "tavily-scandal",
"name": "Tavily - Check Esc\u00e2ndalos"
},
{
"parameters": {
"method": "POST",
"url": "https://api.tavily.com/search",
"sendHeaders": true,
"headerParameters": {
"parameters": [
{
"name": "Content-Type",
"value": "application/json"
}
]
},
"sendBody": true,
"specifyBody": "json",
"jsonBody": "={\n \"api_key\": \"SUA_TAVILY_API_KEY\",\n \"query\": \"{{ $('Loop Over Empresas').item.json.name }} number of employees total staff headcount\",\n \"search_depth\": \"basic\",\n \"max_results\": 3\n}",
"options": {}
},
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 4.3,
"position": [
-640,
160
],
"id": "tavily-employees",
"name": "Tavily - N\u00famero Exato Funcion\u00e1rios"
},
{
"parameters": {
"jsCode": "const company = $('Loop Over Empresas').item.json;\nconst maResults = $('Tavily - Check M&A').item.json;\nconst scandalResults = $('Tavily - Check Esc\u00e2ndalos').item.json;\nconst employeeResults = $('Tavily - N\u00famero Exato Funcion\u00e1rios').item.json;\n\n// --- CHECK M&A ---\nconst maKeywords = ['acquired', 'merger', 'acquisition', 'adquirida', 'fus\u00e3o', 'aquisi\u00e7\u00e3o', 'comprada por'];\nconst maText = JSON.stringify(maResults).toLowerCase();\nconst hasMa = maKeywords.some(k => maText.includes(k));\nconst maStatus = hasMa ? 'Sim - Verificar' : 'N\u00e3o Identificado';\n\n// --- CHECK ESC\u00c2NDALOS ---\nconst scandalKeywords = ['fraud', 'corruption', 'scandal', 'lawsuit', 'investigation', 'fraude', 'corrup\u00e7\u00e3o', 'esc\u00e2ndalo', 'processo', 'investiga\u00e7\u00e3o', 'san\u00e7\u00e3o'];\nconst scandalText = JSON.stringify(scandalResults).toLowerCase();\nconst hasScandal = scandalKeywords.some(k => scandalText.includes(k));\nconst scandalStatus = hasScandal ? 'Sim - Verificar' : 'N\u00e3o Identificado';\n\n// --- N\u00daMERO EXATO DE FUNCION\u00c1RIOS ---\nconst empText = JSON.stringify(employeeResults);\nconst empMatch = empText.match(/(\\d{2,6})\\s*(employees|funcion\u00e1rios|staff|colaboradores)/i);\nconst exactEmployees = empMatch ? empMatch[1] : (company.estimated_num_employees || company.num_employees || 'N\u00e3o encontrado');\n\n// --- FILTROS ---\nconst numEmp = parseInt(exactEmployees) || parseInt(company.estimated_num_employees) || 0;\nconst passesEmployeeFilter = numEmp >= 50;\nconst passesMaFilter = !hasMa;\nconst passesScandalFilter = !hasScandal;\n\nif (!passesEmployeeFilter || !passesMaFilter || !passesScandalFilter) {\n return [];\n}\n\n// --- MONTAR LINHA FINAL ---\nreturn [{\n json: {\n 'Nome da Empresa': company.name || '',\n 'Setor': company.industry || '',\n 'Pa\u00eds': company.hq_location_country || company.country || '',\n 'Cidade': company.hq_location_city || company.city || '',\n 'Website': company.website_url || company.primary_domain || '',\n 'N\u00famero de Funcion\u00e1rios': exactEmployees,\n 'S\u00f3cios / C-Levels': (company.organization_job_postings || []).length > 0 ? 'Ver LinkedIn' : 'N\u00e3o encontrado',\n 'Receita Estimada': company.annual_revenue_printed || 'N\u00e3o encontrado',\n 'Status M&A': maStatus,\n 'Esc\u00e2ndalos': scandalStatus,\n 'Data': new Date().toISOString().split('T')[0]\n }\n}];"
},
"type": "n8n-nodes-base.code",
"typeVersion": 2,
"position": [
-320,
0
],
"id": "filter-001",
"name": "Filtros + Montar Linha"
},
{
"parameters": {
"jsCode": "const items = $input.all();\n\nif (items.length === 0) {\n return [{ json: { message: 'Nenhuma empresa passou pelos filtros.' } }];\n}\n\n// Cabe\u00e7alhos\nconst headers = [\n 'Nome da Empresa',\n 'Setor',\n 'Pa\u00eds',\n 'Cidade',\n 'Website',\n 'N\u00famero de Funcion\u00e1rios',\n 'S\u00f3cios / C-Levels',\n 'Receita Estimada',\n 'Status M&A',\n 'Esc\u00e2ndalos',\n 'Data'\n];\n\n// Montar CSV\nconst rows = items.map(item => {\n return headers.map(h => {\n const val = item.json[h] || '';\n return `\"${String(val).replace(/\"/g, '\"\"')}\"`;\n }).join(',');\n});\n\nconst csv = [headers.join(','), ...rows].join('\\n');\n\nreturn [{\n json: {},\n binary: {\n data: {\n data: Buffer.from(csv).toString('base64'),\n mimeType: 'text/csv',\n fileName: `prospeccao_latam_${new Date().toISOString().split('T')[0]}.csv`,\n fileExtension: 'csv'\n }\n }\n}];"
},
"type": "n8n-nodes-base.code",
"typeVersion": 2,
"position": [
160,
0
],
"id": "excel-001",
"name": "Gerar CSV/Excel"
},
{
"parameters": {
"respondWith": "binary",
"options": {
"responseHeaders": {
"entries": [
{
"name": "Content-Disposition",
"value": "=attachment; filename=\"prospeccao_latam_{{ $now.format('yyyy-MM-dd') }}.csv\""
},
{
"name": "Content-Type",
"value": "text/csv"
}
]
}
}
},
"type": "n8n-nodes-base.respondToWebhook",
"typeVersion": 1.4,
"position": [
400,
0
],
"id": "respond-001",
"name": "Download Excel"
},
{
"parameters": {
"content": "## 1. TRIGGER\nClique em Execute para rodar o workflow manualmente.",
"height": 200,
"width": 240,
"color": 3
},
"type": "n8n-nodes-base.stickyNote",
"typeVersion": 1,
"position": [
-1640,
-160
],
"id": "note-001",
"name": "Nota 1"
},
{
"parameters": {
"content": "## 2. APOLLO\nBusca 100 empresas de Financial Services e M\u00eddia na Am\u00e9rica Latina com 50-500 funcion\u00e1rios.\n\n\u26a0\ufe0f Troque SUA_APOLLO_API_KEY pela sua chave.",
"height": 240,
"width": 280,
"color": 4
},
"type": "n8n-nodes-base.stickyNote",
"typeVersion": 1,
"position": [
-1400,
-200
],
"id": "note-002",
"name": "Nota 2"
},
{
"parameters": {
"content": "## 3. CHECKS via TAVILY\n- M&A: verifica se foi adquirida ou fez aquisi\u00e7\u00f5es\n- Esc\u00e2ndalos: fraude, corrup\u00e7\u00e3o, processos\n- Funcion\u00e1rios: tenta buscar n\u00famero exato\n\n\u26a0\ufe0f Troque SUA_TAVILY_API_KEY pela sua chave.",
"height": 300,
"width": 280,
"color": 7
},
"type": "n8n-nodes-base.stickyNote",
"typeVersion": 1,
"position": [
-880,
-320
],
"id": "note-003",
"name": "Nota 3"
},
{
"parameters": {
"content": "## 4. FILTROS\nEmpresas que N\u00c3O passam s\u00e3o descartadas:\n- Passou por M&A \u2192 fora\n- Tem esc\u00e2ndalo \u2192 fora\n- Menos de 50 funcion\u00e1rios \u2192 fora",
"height": 240,
"width": 260,
"color": 6
},
"type": "n8n-nodes-base.stickyNote",
"typeVersion": 1,
"position": [
-360,
-240
],
"id": "note-004",
"name": "Nota 4"
},
{
"parameters": {
"content": "## 5. OUTPUT\nGera arquivo CSV compat\u00edvel com Excel e disponibiliza para download.",
"height": 200,
"width": 240,
"color": 3
},
"type": "n8n-nodes-base.stickyNote",
"typeVersion": 1,
"position": [
120,
-200
],
"id": "note-005",
"name": "Nota 5"
}
],
"connections": {
"Manual Trigger": {
"main": [
[
{
"node": "Apollo - Buscar Empresas",
"type": "main",
"index": 0
}
]
]
},
"Apollo - Buscar Empresas": {
"main": [
[
{
"node": "Split Empresas",
"type": "main",
"index": 0
}
]
]
},
"Split Empresas": {
"main": [
[
{
"node": "Loop Over Empresas",
"type": "main",
"index": 0
}
]
]
},
"Loop Over Empresas": {
"main": [
[],
[
{
"node": "Tavily - Check M&A",
"type": "main",
"index": 0
},
{
"node": "Tavily - Check Esc\u00e2ndalos",
"type": "main",
"index": 0
},
{
"node": "Tavily - N\u00famero Exato Funcion\u00e1rios",
"type": "main",
"index": 0
}
]
]
},
"Tavily - Check M&A": {
"main": [
[
{
"node": "Filtros + Montar Linha",
"type": "main",
"index": 0
}
]
]
},
"Tavily - Check Esc\u00e2ndalos": {
"main": [
[
{
"node": "Filtros + Montar Linha",
"type": "main",
"index": 1
}
]
]
},
"Tavily - N\u00famero Exato Funcion\u00e1rios": {
"main": [
[
{
"node": "Filtros + Montar Linha",
"type": "main",
"index": 2
}
]
]
},
"Filtros + Montar Linha": {
"main": [
[
{
"node": "Gerar CSV/Excel",
"type": "main",
"index": 0
}
]
]
},
"Gerar CSV/Excel": {
"main": [
[
{
"node": "Download Excel",
"type": "main",
"index": 0
}
]
]
}
},
"active": false,
"settings": {
"executionOrder": "v1"
},
"meta": {
"templateCredsSetupCompleted": false
},
"tags": []
}
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About this workflow
Prospecção Ativa - Financial Services & Mídia LATAM. Uses httpRequest. Scheduled trigger; 15 nodes.
Source: https://gist.github.com/joaozmarchiori-rgb/c42a0c2609bb7d0dc29e5c7d837dcdcd — original creator credit. Request a take-down →
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