{"workflow":{"id":12725,"name":"Verify AI draft answers with Pearl Hybrid Intelligence and OpenAI","views":184,"recentViews":0,"totalViews":184,"createdAt":"2026-01-15T12:22:26.757Z","description":"## Pearl Hybrid Intelligence: AI draft + expert verification (across 100+ expert domains)\n\nDeliver higher-confidence answers by combining an AI assistant with professional human verification.\n\n[Pearl](https://www.pearl.com/enterprise) provides access to a network of **20,000 licensed experts** (including **JDs, MDs, PhDs, DVMs, CPAs, engineers**) across **100+ domains** - Legal and Health are just examples, and the prompts can be tuned for many other areas.\n\n### What this template does\n- Lets users ask questions in a conversational format (your app sends the conversation history).\n- Collects any missing intake details before answering.\n- Generates a clear draft answer using AI.\n- Sends the draft to a Pearl expert for professional verification.\n- Returns the verified answer back to the user, including who verified it.\n\n### How it works (non-technical)\n1. A user asks a question.\n2. If the assistant needs more context, it asks **one focused follow-up question**.\n3. Once the assistant has enough information, it drafts a complete answer.\n4. That draft is automatically reviewed by a qualified Pearl expert.\n5. The user receives the verified answer, along with expert attribution.\n\n### Setup steps (10–15 minutes)\n- Connect your **OpenAI** credential in n8n (used for intake + drafting).\n- Add your **Pearl MCP Server API key** (used for expert verification). You can request a demo access key here:\n  `https://www.pearl.com/enterprise/contact-get-started`\n- Activate the workflow and send a test request using the example payload below.\n\n### Customization\n- The **intake** and **draft answer** prompts can be adjusted to match end-user needs (domain, tone, risk policy, compliance requirements).\n- You can also modify the response format (fields returned, disclaimers, attribution formatting) without changing the core flow.\n\n### Input payload format (conversation history)\nSend a JSON body like:\n\n```json\n{\n  \"model\": \"gpt-4o-mini\",\n  \"messages\": [\n    { \"role\": \"user\", \"content\": \"My question...\" }\n  ]\n}\n","workflow":{"id":"zbpHuVvtlRSOE27NGyyGs","meta":{"instanceId":"fd4293d0fb1498886c9c02308635192359462c03e8b8df89d7768883971c7a80"},"name":"Verify AI draft answers with Pearl Hybrid Intelligence and Open AI","tags":[],"nodes":[{"id":"05107af8-a4e3-4aa0-a1e9-f0ce0ae57148","name":"Overview","type":"n8n-nodes-base.stickyNote","position":[-544,48],"parameters":{"width":528,"height":540,"content":"# Verify AI answers with Pearl Hybrid Intelligence and Open AI\n\n## How it works\n1. A user asks a question.\n2. If anything is missing, the assistant asks one focused follow-up question.\n3. Once ready, the assistant drafts an answer with OpenAI.\n4. The draft is reviewed by a licensed Pearl expert.\n5. The user receives the verified answer with expert attribution.\n\n## Setup steps\n1. Add your OpenAI credential in n8n.\n2. Add your Pearl MCP Server API key (request a demo key at: https://www.pearl.com/enterprise/contact-get-started).\n3. Activate the workflow and call the webhook with your conversation messages.\n4. Adjust the intake + drafting prompts in **Prepare Input** to match your domain and tone."},"typeVersion":1},{"id":"f37c8600-de53-40e3-8a2d-0a2d58158860","name":"Pearl Verify Webhook","type":"n8n-nodes-base.webhook","position":[160,368],"webhookId":"c3de4d5a-8a68-4c3e-9245-f02f64e06562","parameters":{"path":"pearl-verify","options":{},"httpMethod":"POST","responseMode":"responseNode"},"typeVersion":2.1},{"id":"18b2c188-327d-4823-972f-7f0d7f38cf8e","name":"Prepare Input","type":"n8n-nodes-base.code","position":[384,368],"parameters":{"jsCode":"/**\n * n8n Code node (JavaScript)\n * Purpose:\n * - Accept webhook body containing an OpenAI Chat Completions-style `messages` array:\n *     [{ role: \"user\"|\"assistant\"|\"system\", content: \"...\" }, ...]\n * - Construct two message arrays:\n *     1) messagesClarify: system prompt + messages (forces output: END or 1 clarifying question)\n *     2) messagesDraft:   system prompt + messages (produces draft answer)\n */\n\nfunction assertValidMessages(messages) {\n  if (!Array.isArray(messages)) {\n    throw new Error('Request body must include a \"messages\" array.');\n  }\n\n  for (let i = 0; i < messages.length; i++) {\n    const m = messages[i];\n    if (typeof m !== \"object\" || m === null) {\n      throw new Error(`messages[${i}] must be an object.`);\n    }\n    if (typeof m.role !== \"string\" || !m.role.trim()) {\n      throw new Error(`messages[${i}].role must be a non-empty string.`);\n    }\n    if (typeof m.content !== \"string\" || !m.content.trim()) {\n      throw new Error(`messages[${i}].content must be a non-empty string.`);\n    }\n  }\n}\n\nfunction getLastUserMessage(messages) {\n  for (let i = messages.length - 1; i >= 0; i--) {\n    if (messages[i].role === \"user\") return messages[i].content;\n  }\n  return \"\";\n}\n\n// n8n webhook payload can appear as items[0].json.body (Webhook node) or items[0].json (some setups)\nconst input = $input.first() ?? {};\nconst body = input.json.body ?? input;\n\n// Read request fields\nconst messages = body.messages;\nconst openaiModel = body.model || \"gpt-4o-mini\";\n\n// Validate\nassertValidMessages(messages);\n\n// Optional: strip any accidental leading/trailing whitespace\nconst normalizedMessages = messages.map((m) => ({\n  role: m.role.trim(),\n  content: m.content.trim(),\n}));\n\nconst userQuestion = getLastUserMessage(normalizedMessages);\n\n// System prompt: Clarification gate (must output END or a single question)\nconst clarificationSystem = {\n  role: \"system\",\n  content: [\n    \"You are an intake assistant for complex legal and health questions.\",\n    \"\",\n    \"Your job is NOT to answer yet. First decide if you need more context.\",\n    \"\",\n    \"Rules:\",\n    \"1) If you need more information to answer safely/accurately, respond with ONLY the single best clarifying question.\",\n    \"   - No preamble, no bullet points, no multiple questions.\",\n    \"2) If you do NOT need any clarification, respond with EXACTLY this single token: END\",\n    \"\",\n    \"Output must be plain text only.\"\n  ].join(\"\\n\"),\n};\n\n// System prompt: Draft answer generation (used only when clarification returns END)\nconst draftSystem = {\n  role: \"system\",\n  content: [\n    \"You are a helpful assistant.\",\n    \"\",\n    \"Provide a draft answer to the user's question using the full conversation context.\",\n    \"\",\n    \"IMPORTANT SAFETY/QUALITY REQUIREMENTS (health/legal):\",\n    \"- Provide general informational guidance only; do NOT claim to be a professional.\",\n    \"- Encourage consulting a licensed professional for decisions.\",\n    \"- If health: if there are urgent or dangerous symptoms, advise urgent care/emergency services.\",\n    \"- If legal: mention jurisdiction matters and advise consulting a qualified attorney.\",\n    \"\",\n    \"Structure:\",\n    \"1) Short summary\",\n    \"2) Key considerations (bullets)\",\n    \"3) Next steps\"\n  ].join(\"\\n\"),\n};\n\n// Build the two request message arrays\nconst messagesClarify = [clarificationSystem, ...normalizedMessages];\nconst messagesDraft = [draftSystem, ...normalizedMessages];\n\n// Return a single item with fields used by downstream OpenAI HTTP Request nodes\nreturn [\n  {\n    json: {\n      openaiModel,\n      messages: normalizedMessages,\n      userQuestion,\n      messagesClarify,\n      messagesDraft,\n    },\n  },\n];\n"},"typeVersion":2},{"id":"bd546b30-10b0-4b16-91c0-0eae052510b9","name":"OpenAI - Clarify","type":"n8n-nodes-base.httpRequest","position":[608,368],"parameters":{"url":"https://api.openai.com/v1/chat/completions","method":"POST","options":{},"jsonBody":"={{ {\n   \"model\": $json.openaiModel,\n   \"messages\": $json.messagesClarify,\n   \"temperature\": 0\n} }}","sendBody":true,"specifyBody":"json","authentication":"predefinedCredentialType","nodeCredentialType":"openAiApi"},"typeVersion":4.3},{"id":"2ee71615-4cb2-44b9-8930-872ec49adb37","name":"IF - Needs clarification?","type":"n8n-nodes-base.if","position":[832,368],"parameters":{"options":{},"conditions":{"options":{"version":3,"leftValue":"","caseSensitive":true,"typeValidation":"strict"},"combinator":"and","conditions":[{"id":"155eb509-212b-44fb-8240-e6cb2c13c348","operator":{"type":"string","operation":"notEquals"},"leftValue":"={{ $json.choices[0].message.content.trim() }}","rightValue":"END"}]}},"typeVersion":2.3},{"id":"ef4c9f2e-6194-4994-8893-8a50d649a328","name":"Respond: Clarification Question","type":"n8n-nodes-base.respondToWebhook","position":[1056,272],"parameters":{"options":{},"respondWith":"json","responseBody":"={{ {\n  status: 'needs_clarification',\n  clarificationQuestion: $json.choices[0].message.content.trim()\n} }}"},"typeVersion":1.5},{"id":"0e62e22c-5af6-47c4-816b-147172e3f99d","name":"Open AI - Draft Answer","type":"n8n-nodes-base.httpRequest","position":[992,624],"parameters":{"url":"https://api.openai.com/v1/chat/completions","method":"POST","options":{},"jsonBody":"={{ {\n  \"model\": $node['Prepare Input'].json.openaiModel,\n  \"messages\": $node['Prepare Input'].json.messagesDraft,\n  \"temperature\": 0.2\n} }}","sendBody":true,"specifyBody":"json","authentication":"predefinedCredentialType","nodeCredentialType":"openAiApi"},"typeVersion":4.3},{"id":"50264f0c-d972-48ac-9661-3ddd01a958ca","name":"MCP Client","type":"@n8n/n8n-nodes-langchain.mcpClient","position":[1216,624],"parameters":{"tool":{"__rl":true,"mode":"list","value":"verifyAnswer","cachedResultName":"verifyAnswer"},"options":{},"inputMode":"json","jsonInput":"={{ {\n  \"answer\": $json.choices[0].message.content.trim(),\n  \"chatHistory\": $('Prepare Input').item.json.messages\n} }}","endpointUrl":"https://mcp.pearl.com/mcp","authentication":"headerAuth"},"typeVersion":1},{"id":"c5e89c86-8dbd-49ee-83ba-47b7c8f7454d","name":"Respond: Verified Answer by Pearl Expert","type":"n8n-nodes-base.respondToWebhook","position":[1408,624],"parameters":{"options":{},"respondWith":"json","responseBody":"={{ { \n  status: 'verified', \n  answer: $json.content[0].text.answer, \n  verifiedBy: [\n  $json.content?.[0]?.text?.expert?.name,\n  $json.content?.[0]?.text?.expert?.expertise\n].filter(Boolean).join(', ')\n} }}"},"typeVersion":1.5},{"id":"76ac001e-e195-41af-89e8-8ead030182be","name":"Sticky Note","type":"n8n-nodes-base.stickyNote","position":[96,256],"parameters":{"color":7,"width":432,"height":272,"content":"## 1) Intake & prompt setup\nReceives the user conversation and prepares prompts for intake + drafting.\n"},"typeVersion":1},{"id":"6e1aa795-0ac0-466c-904a-fa5272aa8db2","name":"Sticky Note1","type":"n8n-nodes-base.stickyNote","position":[544,256],"parameters":{"color":7,"width":704,"height":272,"content":"## 2) Intake (clarification)\nAsks one follow-up question if more information is needed.\n"},"typeVersion":1},{"id":"2fb6d5ed-147a-4c96-8753-0c7f483aef4b","name":"Sticky Note2","type":"n8n-nodes-base.stickyNote","position":[896,544],"parameters":{"color":7,"width":704,"height":240,"content":"## 3) Draft + expert verification\nDrafts an answer, then sends it to Pearl for professional verification.\n"},"typeVersion":1}],"active":false,"pinData":{},"settings":{"availableInMCP":false,"executionOrder":"v1"},"versionId":"3e782757-99b5-4cee-bd04-9eaaddad1869","connections":{"MCP Client":{"main":[[{"node":"Respond: Verified Answer by Pearl Expert","type":"main","index":0}]]},"Prepare Input":{"main":[[{"node":"OpenAI - 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