{ "id": "tBZGm9I9Tfv4Y2uF", "meta": { "templateCredsSetupCompleted": true }, "name": "Analyze BeyondPresence Video Calls with GPT-4o-mini and Google Sheets", "tags": [ { "id": "9IqkT00CERSl4sHE", "name": "Video Call Agents", "createdAt": "2025-09-12T10:26:08.271Z", "updatedAt": "2025-09-12T10:26:08.271Z" } ], "nodes": [ { "id": "0fe49f1d-8883-4d61-88a5-d8b35068675e", "name": "Workflow Overview", "type": "n8n-nodes-base.stickyNote", "position": [ 176, 0 ], "parameters": { "color": 6, "width": 496, "height": 580, "content": "## \ud83c\udfa5 BeyondPresence Webhook Trigger\n\nThis workflow is triggered when a BeyondPresence video agent call ends. The webhook receives comprehensive call data including:\n\n- Call metadata (participant, duration, timestamps)\n- Complete conversation transcript\n- Initial sentiment analysis\n- Call evaluation metrics\n\nMake sure to configure the webhook URL in your BeyondPresence dashboard under Settings \u2192 Webhooks" }, "typeVersion": 1 }, { "id": "0fd41ccd-19c3-49d9-a3de-2d08b9ea2628", "name": "Processing Steps", "type": "n8n-nodes-base.stickyNote", "position": [ 688, 0 ], "parameters": { "color": 4, "width": 568, "height": 580, "content": "## \ud83d\udd0d Data Validation & AI Analysis\n\n1. **Validate & Enrich Data**: Ensures webhook data integrity and adds calculated fields\n2. **AI Call Analysis**: Uses OpenAI/OpenRouter to generate comprehensive call summary\n3. **Parse AI Response**: Extracts structured JSON from AI response with error handling\n\nThe AI analyzes:\n- Main discussion points\n- Action items & follow-ups\n- Sentiment analysis\n- Key decisions made\n- Questions raised" }, "typeVersion": 1 }, { "id": "e4e8b581-aa56-4ed0-8c75-bb0a26eec3af", "name": "Data Storage", "type": "n8n-nodes-base.stickyNote", "position": [ 1280, 0 ], "parameters": { "color": 3, "width": 392, "height": 580, "content": "## \ud83d\udcca Google Sheets Setup\n\n**Quick Start**:\n1. Copy our template sheet: https://docs.google.com/spreadsheets/d/1TO6-jkCtoSFNLJObtN0UyklgdUd3ZxEnUaNvUaBjpvo/copy\n2. After copying, get your new sheet's ID from the URL\n3. Update the Google Sheets node with your ID\nThe template includes all required columns and sample data!" }, "typeVersion": 1 }, { "id": "0df852bb-3c73-4a5c-acf6-d853b52f5c82", "name": "BeyondPresence Webhook", "type": "n8n-nodes-base.webhook", "position": [ 240, 400 ], "parameters": { "path": "beyondpresence-call-webhook", "options": { "rawBody": false }, "httpMethod": "POST" }, "typeVersion": 2 }, { "id": "7b3ebcb3-e292-432f-9db6-af2fba8f13ad", "name": "Validate & Enrich Data", "type": "n8n-nodes-base.code", "position": [ 752, 400 ], "parameters": { "jsCode": "// Validate incoming webhook data\nconst data = $input.first().json;\nconst startedAt = $('BeyondPresence Webhook').first().json.body.call_data.startedAt;\nconst endedAt = $('BeyondPresence Webhook').first().json.body.call_data.endedAt;\nconst errors = [];\n\n// Check required fields\nif (!data.event_type) errors.push(\"Missing event_type\");\nif (!data.call_id) errors.push(\"Missing call_id\");\nif (!data.user) errors.push(\"Missing user data\");\nif (!data.messages || !Array.isArray(data.messages)) errors.push(\"Missing or invalid messages array\");\n\n// Validate call_data structure\nif (data.call_data) {\n if (!data.user.name) errors.push(\"Missing userName in call_data\");\n if (!startedAt ) errors.push(\"Missing startedAt timestamp\");\n if (!endedAt) errors.push(\"Missing endedAt timestamp\");\n}\n\n// If there are errors, throw with details\nif (errors.length > 0) {\n throw new Error(\"Validation failed: \" + errors.join(\", \"));\n}\n\n// Add calculated fields\nconst startTime = new Date(startedAt);\nconst endTime = new Date(endedAt);\nconst durationMs = endTime - startTime;\nconst durationMinutes = durationMs / 60000;\n\n// Return enriched data\nreturn [{\n json: {\n body: data,\n validation: {\n isValid: true,\n timestamp: new Date().toISOString()\n },\n calculated: {\n durationMinutes: durationMinutes.toFixed(2),\n durationFormatted: formatDuration(durationMs),\n dayOfWeek: startTime.toLocaleDateString('en-US', { weekday: 'long' }),\n timeOfDay: getTimeOfDay(startTime),\n messageCount: data.messages.length,\n hasActionItems: checkForActionItems(data.messages)\n }\n }\n}];\n\n// Helper functions\nfunction formatDuration(ms) {\n const seconds = Math.floor(ms / 1000);\n const minutes = Math.floor(seconds / 60);\n const remainingSeconds = seconds % 60;\n return `${minutes}m ${remainingSeconds}s`;\n}\n\nfunction getTimeOfDay(date) {\n const hour = date.getHours();\n if (hour < 6) return \"Early Morning\";\n if (hour < 12) return \"Morning\";\n if (hour < 17) return \"Afternoon\";\n if (hour < 21) return \"Evening\";\n return \"Night\";\n}\n\nfunction checkForActionItems(messages) {\n const actionKeywords = ['will do', 'action item', 'follow up', 'next step', 'todo', 'task'];\n return messages.some(msg => \n actionKeywords.some(keyword => \n msg.message.toLowerCase().includes(keyword)\n )\n );\n}" }, "typeVersion": 2, "continueOnFail": true }, { "id": "4593d36b-6879-42f7-ada2-1853e4c500aa", "name": "AI Call Analysis", "type": "@n8n/n8n-nodes-langchain.openAi", "position": [ 944, 400 ], "parameters": { "modelId": { "__rl": true, "mode": "id", "value": "gpt-4o-mini" }, "options": { "topP": 0.9, "temperature": 0.3 }, "messages": { "values": [ { "role": "system", "content": "=You are an expert conversation analyst. Analyze the following call data and provide a comprehensive summary.\n\nCONTEXT:\n- Current Date/Time: {{ $now.format('HH:mm dd.mm.yyyy') }}\n- Participant: {{$json.body.user.name }}\n- Call Duration: {{ $json.calculated.durationMinutes }} minutes\n- Time of Day: {{ $json.calculated.timeOfDay }}\n- Day of Week: {{ $json.calculated.dayOfWeek }}\n- Message Count: {{ $json.calculated.messageCount }}\n\nCONVERSATION DATA:\n{{ $json.body.messages.map(m => `[${m.sent_at}] ${m.sender.toUpperCase()}: ${m.message}`).join('\\n') }}\n\nANALYSIS REQUIREMENTS:\n1. Extract factual information only from the provided data\n2. If a section has no relevant content, use \"Not applicable\"\n3. Identify specific commitments, dates, and actions mentioned\n4. Analyze emotional tone and engagement level\n5. Note any technical issues or interruptions\n\nOUTPUT FORMAT (strict JSON):\n```json\n{\n \"title\": \"Brief, descriptive title (max 80 chars)\",\n \"metadata\": {\n \"participant\": \"exact name from data\",\n \"date\": \"ISO format date\",\n \"duration_minutes\": \"number as string\",\n \"topic\": \"main discussion topic\",\n \"user_sentiment\": \"satisfied/neutral/dissatisfied\",\n \"engagement_level\": \"high/medium/low\"\n },\n \"summary\": \"2-3 sentence executive summary of the conversation\",\n \"main_points\": [\"up to 5 key discussion points\"],\n \"action_items\": [\n {\"task\": \"specific action\", \"owner\": \"person responsible\", \"due_date\": \"ISO date or TBD\"}\n ],\n \"follow_ups\": [\"specific next steps mentioned\"],\n \"key_decisions\": [\"decisions made during call\"],\n \"questions_raised\": [\"unresolved questions\"],\n \"stories\": [\"any anecdotes or examples shared\"],\n \"references\": [\"external resources or documents mentioned\"],\n \"arguments\": [\n {\"point\": \"argument made\", \"counterpoint\": \"opposing view if any\"}\n ],\n \"related_topics\": [\"topics that came up in discussion\"],\n \"sentiment_analysis\": {\n \"overall\": \"positive/neutral/negative\",\n \"confidence\": \"high/medium/low\",\n \"turning_points\": [\"moments where sentiment changed\"],\n \"key_emotional_indicators\": [\"specific phrases indicating emotion\"]\n },\n \"recommendations\": [\"suggested actions based on analysis\"]\n}\n```\n\nRules:\n1. Use ONLY data from the provided conversation\n2. For empty sections, use empty arrays [] or \"Not applicable\"\n3. All dates should be in ISO 8601 format\n4. Be specific and actionable in recommendations" }, { "content": "=Analyze this BeyondPresence video agent call:\n\nCall Data: {{ $('BeyondPresence Webhook').item.json.body.call_data.toJsonString() }}\nEvaluation: {{ $('BeyondPresence Webhook').item.json.body.evaluation.toJsonString() }}\nMessages: {{ JSON.stringify($json.body.messages) }}\n\nProvide the analysis in the exact JSON format specified." } ] } }, "credentials": { "openAiApi": { "name": "" } }, "typeVersion": 1 }, { "id": "95b5df2f-9a6c-4e39-9442-5a7228d95bdb", "name": "Save to Google Sheets", "type": "n8n-nodes-base.googleSheets", "position": [ 1504, 400 ], "parameters": { "columns": { "value": { "Date": "={{ $json.metadata.date }}", "Title": "={{ $json.title }}", "Topic": "={{ $json.metadata.topic }}", "Story 1": "={{ $json.stories }}", "Summary": "={{ $json.summary }}", "Argument 1": "={{ $json.references[0] }}", "Argument 2": "={{ $json.references[1] }}", "Follow Up 1": "={{ $json.follow_ups[0] }}", "Follow Up 2": "={{ $json.follow_ups[1] }}", "Participant": "={{ $json.metadata.participant }}", "Reference 1": "={{ $json.references[0] }}", "Reference 2": "={{ $json.references[1]}}", "Main Point 1": "={{ $json.main_points[0] }}", "Main Point 2": "={{ $json.main_points[1] }}", "Main Point 3": "={{ $json.main_points[2] }}", "Action Item 1": "={{ $json.action_items[0]}}", "Action Item 2": "={{ $json.action_items[1] }}", "User Sentiment": "={{ $json.metadata.user_sentiment }}", "Related Topic 1": "={{ $json.related_topics[0] }}", "Related Topic 2": "={{ $json.related_topics[1] }}", "Related Topic 3": "={{ $json.related_topics[2] }}", "Sentiment Overall": "={{ $json.sentiment_analysis.overall }}", "Duration (minutes)": "={{ $json.metadata.duration_minutes }}", "Sentiment Confidence": "={{ $json.sentiment_analysis.confidence }}", "Emotional Indicator 1": "={{ $json.sentiment_analysis.key_emotional_indicators[0]}}", "Emotional Indicator 2": "={{ $json.sentiment_analysis.key_emotional_indicators[1]}}" }, "schema": [ { "id": "Title", "type": "string", "display": true, "required": false, "displayName": "Title", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "Participant", "type": "string", "display": true, "required": false, "displayName": "Participant", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "Date", "type": "string", "display": true, "required": false, "displayName": "Date", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "Duration (minutes)", "type": "string", "display": true, "required": false, "displayName": "Duration (minutes)", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "Topic", "type": "string", "display": true, "required": false, "displayName": "Topic", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "User Sentiment", "type": "string", "display": true, "required": false, "displayName": "User Sentiment", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "Summary", "type": "string", "display": true, "required": false, "displayName": "Summary", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "Main Point 1", "type": "string", "display": true, "required": false, "displayName": "Main Point 1", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "Main Point 2", "type": "string", "display": true, "required": false, "displayName": "Main Point 2", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "Main Point 3", "type": "string", "display": true, "required": false, "displayName": "Main Point 3", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "Action Item 1", "type": "string", "display": true, "required": false, "displayName": "Action Item 1", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "Action Due 1", "type": "string", "display": true, "required": false, "displayName": "Action Due 1", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "Action Item 2", "type": "string", "display": true, "required": false, "displayName": "Action Item 2", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "Action Due 2", "type": "string", "display": true, "required": false, "displayName": "Action Due 2", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "Follow Up 1", "type": "string", "display": true, "required": false, "displayName": "Follow Up 1", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "Follow Up 2", "type": "string", "display": true, "required": false, "displayName": "Follow Up 2", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "Story 1", "type": "string", "display": true, "required": false, "displayName": "Story 1", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "Reference 1", "type": "string", "display": true, "required": false, "displayName": "Reference 1", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "Reference 2", "type": "string", "display": true, "required": false, "displayName": "Reference 2", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "Argument 1", "type": "string", "display": true, "required": false, "displayName": "Argument 1", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "Counterpoint 1", "type": "string", "display": true, "required": false, "displayName": "Counterpoint 1", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "Argument 2", "type": "string", "display": true, "required": false, "displayName": "Argument 2", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "Counterpoint 2", "type": "string", "display": true, "required": false, "displayName": "Counterpoint 2", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "Related Topic 1", "type": "string", "display": true, "required": false, "displayName": "Related Topic 1", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "Related Topic 2", "type": "string", "display": true, "required": false, "displayName": "Related Topic 2", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "Related Topic 3", "type": "string", "display": true, "required": false, "displayName": "Related Topic 3", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "Sentiment Overall", "type": "string", "display": true, "required": false, "displayName": "Sentiment Overall", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "Sentiment Confidence", "type": "string", "display": true, "required": false, "displayName": "Sentiment Confidence", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "Emotional Indicator 1", "type": "string", "display": true, "required": false, "displayName": "Emotional Indicator 1", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "Emotional Indicator 2", "type": "string", "display": true, "required": false, "displayName": "Emotional Indicator 2", "defaultMatch": false, "canBeUsedToMatch": true } ], "mappingMode": "defineBelow", "matchingColumns": [], "attemptToConvertTypes": false, "convertFieldsToString": false }, "options": {}, "operation": "append", "sheetName": { "__rl": true, "mode": "list", "value": "gid=0", "cachedResultUrl": "https://docs.google.com/spreadsheets/d/1TO6-jkCtoSFNLJObtN0UyklgdUd3ZxEnUaNvUaBjpvo/edit#gid=0", "cachedResultName": "Sheet1" }, "documentId": { "__rl": true, "mode": "list", "value": "1TO6-jkCtoSFNLJObtN0UyklgdUd3ZxEnUaNvUaBjpvo", "cachedResultUrl": "https://docs.google.com/spreadsheets/d/1TO6-jkCtoSFNLJObtN0UyklgdUd3ZxEnUaNvUaBjpvo/edit?usp=drivesdk", "cachedResultName": "BeyondPresence Call Analytics Template" } }, "credentials": { "googleSheetsOAuth2Api": { "name": "" } }, "typeVersion": 4.6 }, { "id": "6084e6a2-3ef5-4968-88da-707fd75373b1", "name": "Extension Options", "type": "n8n-nodes-base.stickyNote", "position": [ 1696, 0 ], "parameters": { "color": 5, "width": 320, "height": 580, "content": "## \ud83d\udd14 Optional Extensions\n\n**Slack Notification**:\n- Send summary to team channel\n- Alert on negative sentiment\n- Notify about action items\n\n**Database Backup**:\n- Store in PostgreSQL/MySQL\n- Enable advanced analytics\n- Create dashboards\n\n**CRM Integration**:\n- Update contact records\n- Create follow-up tasks\n- Log call activities" }, "typeVersion": 1 }, { "id": "03ead4a1-3b18-4c48-8cc8-13021a7c2de4", "name": "Handle webhook event", "type": "n8n-nodes-beyondpresence.beyondPresence", "position": [ 480, 400 ], "parameters": { "resource": "webhook", "eventType": "call_ended", "webhookData": "={{ $json.body.toJsonString() }}" }, "credentials": { "beyondPresenceApi": { "name": "" } }, "typeVersion": 1 }, { "id": "b50096f9-f930-4c06-9052-3fef621a2061", "name": "Parse AI Response", "type": "n8n-nodes-base.code", "position": [ 1312, 400 ], "parameters": { "jsCode": "// Get the content string from the OpenAI response\nconst content = $input.first().json.message.content;\n\n// Use a regular expression to extract the JSON inside the code block\n// This matches content between ```json and ``` or just between ``` and ```\nconst match = content.match(/```(?:json)?\\s*([\\s\\S]*?)```/);\n\nif (!match || !match[1]) {\n // If no match with code block, try to extract JSON directly from the content\n // Sometimes the response might have JSON without code blocks\n const directJsonMatch = content.match(/\\{[\\s\\S]*\\}/);\n if (directJsonMatch) {\n try {\n return [{ json: JSON.parse(directJsonMatch[0]) }];\n } catch (e) {\n throw new Error('Found potential JSON but failed to parse it: ' + e.message);\n }\n }\n throw new Error('No JSON code block found in content.');\n}\n\n// Clean up the JSON string\nlet jsonString = match[1]\n .replace(/\\/\\/.*$/gm, '') // Remove single-line comments\n .replace(/\\/\\*[\\s\\S]*?\\*\\//g, '') // Remove multi-line comments\n .replace(/,(\\s*[}\\]])/g, '$1') // Remove trailing commas\n .trim(); // Trim whitespace\n\nlet parsed;\ntry {\n parsed = JSON.parse(jsonString);\n} catch (e) {\n // If initial parse fails, try a more aggressive cleaning approach\n try {\n // Try to fix common JSON errors\n jsonString = jsonString\n .replace(/(['\"])?([a-zA-Z0-9_]+)(['\"])?\\s*:/g, '\"$2\":') // Ensure property names are quoted\n .replace(/:\\s*'([^']*)'/g, ':\"$1\"'); // Replace single quotes with double quotes\n \n parsed = JSON.parse(jsonString);\n } catch (fallbackError) {\n throw new Error('Failed to parse JSON: ' + e.message + \n '\\nExtracted string:\\n' + jsonString);\n }\n}\n\nreturn [{ json: parsed }];" }, "typeVersion": 2, "continueOnFail": true } ], "active": false, "settings": { "executionOrder": "v1" }, "versionId": "9212cd25-fc88-4f43-8e21-85e6f7b0f311", "connections": { "AI Call Analysis": { "main": [ [ { "node": "Parse AI Response", "type": "main", "index": 0 } ] ] }, "Parse AI Response": { "main": [ [ { "node": "Save to Google Sheets", "type": "main", "index": 0 } ] ] }, "Handle webhook event": { "main": [ [ { "node": "Validate & Enrich Data", "type": "main", "index": 0 } ] ] }, "BeyondPresence Webhook": { "main": [ [ { "node": "Handle webhook event", "type": "main", "index": 0 } ] ] }, "Validate & Enrich Data": { "main": [ [ { "node": "AI Call Analysis", "type": "main", "index": 0 } ] ] } } }