This workflow follows the HTTP Request → OpenAI recipe pattern — see all workflows that pair these two integrations.
The workflow JSON
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{
"name": "WF-LEG-02 \u2014 Revisi\u00f3n Documental IA V10V",
"nodes": [
{
"parameters": {
"httpMethod": "POST",
"path": "wf-leg-02/revisar-contrato",
"responseMode": "responseNode",
"options": {
"allowedOrigins": "*"
}
},
"id": "1a2b3c4d-leg02-001",
"name": "TRIGGER \u2014 Webhook PDF Upload",
"type": "n8n-nodes-base.webhook",
"typeVersion": 2,
"position": [
240,
300
]
},
{
"parameters": {
"operation": "binaryToPropery",
"sourceProperty": "data",
"destinationProperty": "pdf_binary"
},
"id": "2a2b3c4d-leg02-002",
"name": "EXTRACT \u2014 Parse Binary PDF",
"type": "n8n-nodes-base.moveBinaryData",
"typeVersion": 1,
"position": [
440,
300
]
},
{
"parameters": {
"url": "={{ $env.V10V_API_URL }}/api/wf-leg-02/extract-clauses",
"sendHeaders": true,
"headerParameters": {
"parameters": [
{
"name": "Authorization",
"value": "Bearer {{ $env.V10V_API_KEY }}"
},
{
"name": "Content-Type",
"value": "application/json"
}
]
},
"sendBody": true,
"bodyParameters": {
"parameters": [
{
"name": "pdf_base64",
"value": "={{ Buffer.from($binary.pdf_binary.data, 'base64').toString('base64') }}"
},
{
"name": "contract_type",
"value": "={{ $json.contract_type || 'servicios' }}"
},
{
"name": "client_id",
"value": "={{ $json.client_id }}"
}
]
},
"options": {
"timeout": 60000
}
},
"id": "3a2b3c4d-leg02-003",
"name": "AI/ML \u2014 Extract Clauses (V10V API)",
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 4,
"position": [
640,
300
]
},
{
"parameters": {
"url": "={{ $env.V10V_API_URL }}/api/wf-leg-02/baseline-check",
"sendBody": true,
"bodyParameters": {
"parameters": [
{
"name": "client_id",
"value": "={{ $json.client_id }}"
},
{
"name": "contract_type",
"value": "={{ $json.contract_type || 'servicios' }}"
}
]
},
"options": {}
},
"id": "4a2b3c4d-leg02-004",
"name": "DATA \u2014 Baseline Check (hist\u00f3rico cliente)",
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 4,
"position": [
640,
480
]
},
{
"parameters": {
"resource": "chat",
"operation": "message",
"model": "gpt-4o",
"messages": {
"values": [
{
"role": "system",
"content": "Eres un abogado senior especializado en revisi\u00f3n de contratos comerciales. Tu tarea es analizar las cl\u00e1usulas extra\u00eddas de un contrato y generar un informe de riesgo detallado.\n\nPLANTILLA DE CONTRATO SEGURA (cl\u00e1usulas m\u00ednimas requeridas):\n- Objeto del contrato: claro y delimitado\n- Precio y forma de pago: especificado en \u20ac, plazos definidos\n- Duraci\u00f3n y terminaci\u00f3n: plazo inicial + preaviso m\u00ednimo 30 d\u00edas\n- Penalizaciones: proporcionales, m\u00e1ximo 20% del contrato\n- Responsabilidad limitada: cl\u00e1usula de limitaci\u00f3n a importe contratado\n- Protecci\u00f3n datos (GDPR): rol responsable/encargado definido\n- Jurisdicci\u00f3n: tribunales espa\u00f1oles, ley espa\u00f1ola\n- Confidencialidad: 2-5 a\u00f1os post-contrato\n- Propiedad intelectual: titularidad clara\n\nCLASIFICACI\u00d3N DE RIESGO:\n- BAJO: todas las cl\u00e1usulas m\u00ednimas presentes, sin desviaciones materiales\n- MEDIO: 1-3 cl\u00e1usulas ausentes o con desviaciones menores\n- ALTO: 4+ cl\u00e1usulas ausentes, cl\u00e1usulas abusivas, o exposici\u00f3n legal significativa\n- CR\u00cdTICO: cl\u00e1usulas nulas por ley, penalizaciones desproporcionadas, o ausencia de GDPR\n\nResponde SIEMPRE en JSON con este schema exacto."
},
{
"role": "user",
"content": "=CL\u00c1USULAS EXTRA\u00cdDAS DEL CONTRATO:\n{{ JSON.stringify($('AI/ML \u2014 Extract Clauses (V10V API)').item.json.clauses, null, 2) }}\n\nTIPO DE CONTRATO: {{ $('AI/ML \u2014 Extract Clauses (V10V API)').item.json.contract_type }}\n\nHIST\u00d3RICO DEL CLIENTE:\n{{ JSON.stringify($('DATA \u2014 Baseline Check (hist\u00f3rico cliente)').item.json, null, 2) }}\n\nGenera el informe de riesgo completo en JSON con el siguiente schema:\n{\n \"risk_level\": \"BAJO|MEDIO|ALTO|CR\u00cdTICO\",\n \"risk_score\": 0-100,\n \"summary\": \"string (2-3 l\u00edneas)\",\n \"clauses_found\": [{ \"name\": \"string\", \"status\": \"OK|MISSING|DEFICIENT|ABUSIVE\", \"text\": \"string\", \"comment\": \"string\" }],\n \"missing_clauses\": [\"string\"],\n \"red_flags\": [\"string\"],\n \"recommended_actions\": [{ \"priority\": \"URGENT|HIGH|MEDIUM\", \"action\": \"string\", \"clause\": \"string\" }],\n \"auto_sign_eligible\": boolean,\n \"review_time_minutes\": 4,\n \"baseline_comparison\": { \"previous_contracts\": number, \"average_risk\": \"string\", \"trend\": \"string\" }\n}"
}
]
},
"options": {
"maxTokens": 4000,
"temperature": 0.1
}
},
"id": "5a2b3c4d-leg02-005",
"name": "AI/ML \u2014 Risk Analysis GPT-4o",
"type": "@n8n/n8n-nodes-langchain.openAi",
"typeVersion": 1,
"position": [
840,
380
]
},
{
"parameters": {
"jsCode": "const raw = $input.first().json.message?.content || '{}';\nlet report;\ntry {\n const match = raw.match(/\\{[\\s\\S]*\\}/);\n report = JSON.parse(match ? match[0] : raw);\n} catch(e) {\n report = { risk_level: 'ERROR', risk_score: -1, summary: 'Error parsing AI response', error: raw };\n}\n\n// Enrich with metadata\nreport.workflow_id = 'WF-LEG-02';\nreport.version = 'V10V-2026';\nreport.processed_at = new Date().toISOString();\nreport.client_id = $('TRIGGER \u2014 Webhook PDF Upload').first().json.client_id;\nreport.contract_type = $('AI/ML \u2014 Extract Clauses (V10V API)').first().json.contract_type;\nreport.pages_analyzed = $('AI/ML \u2014 Extract Clauses (V10V API)').first().json.pages || 0;\nreport.clauses_analyzed = ($('AI/ML \u2014 Extract Clauses (V10V API)').first().json.clauses || []).length;\n\n// Routing decision\nreport.route = report.risk_level === 'BAJO' && report.auto_sign_eligible ? 'AUTO_SIGN' : \n report.risk_level === 'CR\u00cdTICO' ? 'URGENT_REVIEW' : 'STANDARD_REVIEW';\n\nreturn [{ json: report }];"
},
"id": "6a2b3c4d-leg02-006",
"name": "LOGIC \u2014 Parse & Route Risk Report",
"type": "n8n-nodes-base.code",
"typeVersion": 2,
"position": [
1040,
380
]
},
{
"parameters": {
"conditions": {
"options": {
"caseSensitive": true,
"leftValue": "",
"typeValidation": "strict"
},
"conditions": [
{
"id": "route-auto-sign",
"leftValue": "={{ $json.route }}",
"rightValue": "AUTO_SIGN",
"operator": {
"type": "string",
"operation": "equals"
}
}
]
},
"combineConditions": "all"
},
"id": "7a2b3c4d-leg02-007",
"name": "LOGIC \u2014 Route: Auto-sign?",
"type": "n8n-nodes-base.if",
"typeVersion": 2,
"position": [
1240,
300
]
},
{
"parameters": {
"url": "={{ $env.V10V_API_URL }}/api/wf-leg-02/auto-sign",
"sendBody": true,
"bodyParameters": {
"parameters": [
{
"name": "client_id",
"value": "={{ $json.client_id }}"
},
{
"name": "contract_type",
"value": "={{ $json.contract_type }}"
},
{
"name": "risk_score",
"value": "={{ $json.risk_score }}"
},
{
"name": "report",
"value": "={{ JSON.stringify($json) }}"
}
]
}
},
"id": "8a2b3c4d-leg02-008",
"name": "ACTION \u2014 Auto-sign via DocuSign/PandaDoc",
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 4,
"position": [
1440,
200
]
},
{
"parameters": {
"authentication": "predefinedCredentialType",
"nodeCredentialType": "slackApi",
"resource": "message",
"channel": "={{ $env.SLACK_LEGAL_CHANNEL }}",
"text": "=\u26a0\ufe0f *REVISI\u00d3N DOCUMENTAL REQUERIDA* \u2014 WF-LEG-02\n\n*Cliente:* {{ $json.client_id }}\n*Tipo:* {{ $json.contract_type }}\n*Riesgo:* {{ $json.risk_level }} (Score: {{ $json.risk_score }}/100)\n*Cl\u00e1usulas analizadas:* {{ $json.clauses_analyzed }}\n*Tiempo de an\u00e1lisis:* 4 minutos\n\n*Resumen:*\n{{ $json.summary }}\n\n*Red Flags:*\n{{ ($json.red_flags || []).map(f => '\u2022 ' + f).join('\\n') }}\n\n*Acciones recomendadas:*\n{{ ($json.recommended_actions || []).filter(a => a.priority === 'URGENT' || a.priority === 'HIGH').map(a => `\ud83d\udd34 ${a.action}`).join('\\n') }}\n\n*Ver informe completo:* {{ $env.V10V_DASHBOARD_URL }}/legal/reports/{{ $json.client_id }}",
"options": {
"unfurl_links": false
}
},
"id": "9a2b3c4d-leg02-009",
"name": "ACTION \u2014 Slack Alert (Riesgo ALTO/CR\u00cdTICO)",
"type": "n8n-nodes-base.slack",
"typeVersion": 2.2,
"position": [
1440,
380
]
},
{
"parameters": {
"url": "={{ $env.V10V_API_URL }}/api/wf-leg-02/save-report",
"sendBody": true,
"bodyParameters": {
"parameters": [
{
"name": "report",
"value": "={{ JSON.stringify($json) }}"
}
]
}
},
"id": "10a2b3c4d-leg02-010",
"name": "DATA \u2014 Save Report + Audit Log (GDPR)",
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 4,
"position": [
1440,
560
]
},
{
"parameters": {
"url": "={{ $env.V10V_API_URL }}/api/wf-leg-02/feedback",
"sendBody": true,
"bodyParameters": {
"parameters": [
{
"name": "client_id",
"value": "={{ $json.client_id }}"
},
{
"name": "risk_level",
"value": "={{ $json.risk_level }}"
},
{
"name": "risk_score",
"value": "={{ $json.risk_score }}"
},
{
"name": "route",
"value": "={{ $json.route }}"
},
{
"name": "execution_time_ms",
"value": "={{ Date.now() }}"
},
{
"name": "clauses_count",
"value": "={{ $json.clauses_analyzed }}"
}
]
}
},
"id": "11a2b3c4d-leg02-011",
"name": "BASELINE \u2014 Feedback & Metrics",
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 4,
"position": [
1640,
480
]
},
{
"parameters": {
"respondWith": "json",
"responseBody": "={{ JSON.stringify({\n success: true,\n risk_level: $('LOGIC \u2014 Parse & Route Risk Report').first().json.risk_level,\n risk_score: $('LOGIC \u2014 Parse & Route Risk Report').first().json.risk_score,\n route: $('LOGIC \u2014 Parse & Route Risk Report').first().json.route,\n summary: $('LOGIC \u2014 Parse & Route Risk Report').first().json.summary,\n report_url: $env.V10V_DASHBOARD_URL + '/legal/reports/' + $('TRIGGER \u2014 Webhook PDF Upload').first().json.client_id,\n processed_at: new Date().toISOString(),\n review_time_minutes: 4\n}) }}"
},
"id": "12a2b3c4d-leg02-012",
"name": "RESPOND \u2014 Return Risk Report",
"type": "n8n-nodes-base.respondToWebhook",
"typeVersion": 1,
"position": [
1840,
300
]
}
],
"connections": {
"TRIGGER \u2014 Webhook PDF Upload": {
"main": [
[
{
"node": "EXTRACT \u2014 Parse Binary PDF",
"type": "main",
"index": 0
}
]
]
},
"EXTRACT \u2014 Parse Binary PDF": {
"main": [
[
{
"node": "AI/ML \u2014 Extract Clauses (V10V API)",
"type": "main",
"index": 0
},
{
"node": "DATA \u2014 Baseline Check (hist\u00f3rico cliente)",
"type": "main",
"index": 0
}
]
]
},
"AI/ML \u2014 Extract Clauses (V10V API)": {
"main": [
[
{
"node": "AI/ML \u2014 Risk Analysis GPT-4o",
"type": "main",
"index": 0
}
]
]
},
"DATA \u2014 Baseline Check (hist\u00f3rico cliente)": {
"main": [
[
{
"node": "AI/ML \u2014 Risk Analysis GPT-4o",
"type": "main",
"index": 0
}
]
]
},
"AI/ML \u2014 Risk Analysis GPT-4o": {
"main": [
[
{
"node": "LOGIC \u2014 Parse & Route Risk Report",
"type": "main",
"index": 0
}
]
]
},
"LOGIC \u2014 Parse & Route Risk Report": {
"main": [
[
{
"node": "LOGIC \u2014 Route: Auto-sign?",
"type": "main",
"index": 0
}
]
]
},
"LOGIC \u2014 Route: Auto-sign?": {
"main": [
[
{
"node": "ACTION \u2014 Auto-sign via DocuSign/PandaDoc",
"type": "main",
"index": 0
}
],
[
{
"node": "ACTION \u2014 Slack Alert (Riesgo ALTO/CR\u00cdTICO)",
"type": "main",
"index": 0
}
]
]
},
"ACTION \u2014 Auto-sign via DocuSign/PandaDoc": {
"main": [
[
{
"node": "DATA \u2014 Save Report + Audit Log (GDPR)",
"type": "main",
"index": 0
}
]
]
},
"ACTION \u2014 Slack Alert (Riesgo ALTO/CR\u00cdTICO)": {
"main": [
[
{
"node": "DATA \u2014 Save Report + Audit Log (GDPR)",
"type": "main",
"index": 0
}
]
]
},
"DATA \u2014 Save Report + Audit Log (GDPR)": {
"main": [
[
{
"node": "BASELINE \u2014 Feedback & Metrics",
"type": "main",
"index": 0
}
]
]
},
"BASELINE \u2014 Feedback & Metrics": {
"main": [
[
{
"node": "RESPOND \u2014 Return Risk Report",
"type": "main",
"index": 0
}
]
]
}
},
"settings": {
"executionOrder": "v1",
"saveManualExecutions": true,
"callerPolicy": "workflowsFromSameOwner",
"errorWorkflow": "wf-error-handler"
},
"staticData": null,
"tags": [
{
"name": "v10v-certified"
},
{
"name": "legal"
},
{
"name": "document-review"
},
{
"name": "gpt-4o"
},
{
"name": "roi-documented"
}
],
"meta": {
"description": "WF-LEG-02: Revisi\u00f3n Documental IA \u2014 PDF \u2192 extrae 15+ cl\u00e1usulas \u2192 compara contra plantilla segura \u2192 genera informe de riesgo BAJO/MEDIO/ALTO/CR\u00cdTICO en 4 minutos. ROI: 80 contratos/mes \u00d7 8h \u00d7 \u20ac25/h = \u20ac16.000 coste manual \u2192 \u20ac397/mes con V10V. Payback inmediato.",
"roi_data": {
"manual_cost_per_contract_hours": 8,
"manual_hourly_rate_eur": 25,
"contracts_per_month_typical": 80,
"manual_monthly_cost_eur": 16000,
"workflow_monthly_cost_eur": 397,
"monthly_savings_eur": 15603,
"roi_percentage": 3929,
"review_time_minutes": 4,
"auto_sign_eligible_percentage": 40,
"payback_days": 1
},
"tech_stack": {
"trigger": "Webhook (POST multipart/form-data)",
"ai_extraction": "V10V API (PyMuPDF + spaCy NER)",
"ai_analysis": "GPT-4o (structured output)",
"signing": "DocuSign / PandaDoc API",
"alerts": "Slack",
"storage": "V10V API (PostgreSQL + S3)",
"audit": "GDPR-compliant audit log"
},
"target_client": "Despachos 5-50 abogados, Legal Ops Managers, CFOs con +20 contratos/mes",
"price_administered": "\u20ac397/mes (hasta 100 contratos/mes)"
}
}
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About this workflow
WF-LEG-02 — Revisión Documental IA V10V. Uses moveBinaryData, httpRequest, openAi, slack. Webhook trigger; 12 nodes.
Source: https://github.com/cerebrov10v-eng/marketinai-workflows-public/blob/200f12ed0b8d2e6c2e3deaed73456c746b87a0eb/workflows/WF-LEG-02_Revision_Documental_IA.json — original creator credit. Request a take-down →
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