{ "name": "Patent Filing Velocity Tracker", "nodes": [ { "parameters": { "path": "run-patent-pipeline", "httpMethod": "GET", "responseMode": "responseNode", "options": {} }, "id": "webhook-trigger", "name": "Manual Run Trigger", "type": "n8n-nodes-base.webhook", "typeVersion": 2, "position": [ -4400, 0 ] }, { "parameters": { "path": "patent-dashboard", "httpMethod": "GET", "responseMode": "responseNode", "options": {} }, "id": "dashboard-webhook", "name": "Dashboard Webhook", "type": "n8n-nodes-base.webhook", "typeVersion": 2, "position": [ -4400, 240 ] }, { "parameters": { "jsCode": "// Fetch Patents — AI Chips Category\n// USPTO PatentsView API — free, no auth required\n// Companies: NVIDIA, AMD, Intel, Google, Apple\n// CPC codes for AI chips: G06N (ML/AI) + H01L (semiconductor devices)\n\nconst companies = [\n { name: 'NVIDIA', aliases: ['NVIDIA Corporation', 'NVIDIA Corp', 'Nvidia'] },\n { name: 'AMD', aliases: ['Advanced Micro Devices', 'Advanced Micro Devices Inc', 'AMD'] },\n { name: 'Intel', aliases: ['Intel Corporation', 'Intel Corp', 'Intel'] },\n { name: 'Google', aliases: ['Google LLC', 'Google Inc', 'Alphabet', 'DeepMind'] },\n { name: 'Apple', aliases: ['Apple Inc', 'Apple Computer', 'Apple'] }\n];\n\nconst CPC_CODES = ['G06N', 'H01L'];\n\n// Calculate date range — last 8 quarters\nconst now = new Date();\nconst eightQuartersAgo = new Date(now);\neightQuartersAgo.setFullYear(eightQuartersAgo.getFullYear() - 2);\nconst dateFrom = eightQuartersAgo.toISOString().split('T')[0];\nconst dateTo = now.toISOString().split('T')[0];\n\nconst results = [];\n\nfor (const company of companies) {\n for (const alias of company.aliases) {\n try {\n const query = {\n _and: [\n { _or: CPC_CODES.map(code => ({ cpc_section_id: { _text_phrase: code } })) },\n { assignee_organization: { _text_phrase: alias } },\n { patent_date: { _gte: dateFrom, _lte: dateTo } }\n ]\n };\n\n const url = 'https://api.patentsview.org/patents/query';\n const body = {\n q: query,\n f: ['patent_id', 'patent_title', 'patent_abstract', 'patent_date', \n 'assignee_organization', 'inventor_last_name', 'inventor_first_name',\n 'cpc_section_id', 'cpc_subgroup_id'],\n o: { per_page: 100, page: 1 }\n };\n\n const response = await $helpers.httpRequest({\n method: 'POST',\n url,\n headers: { 'Content-Type': 'application/json' },\n body: JSON.stringify(body)\n });\n\n const data = JSON.parse(response);\n const patents = data.patents || [];\n\n if (patents.length > 0) {\n results.push({\n company: company.name,\n alias,\n patents,\n fetchedAt: new Date().toISOString()\n });\n }\n } catch (e) {\n results.push({\n company: company.name,\n alias,\n patents: [],\n error: e.message\n });\n }\n }\n}\n\nreturn [{ json: { rawResults: results, fetchedAt: new Date().toISOString() } }];\n" }, "id": "fetch-patents", "name": "Fetch Patent Data", "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ -4160, 0 ] }, { "parameters": { "jsCode": "// Node 1A — Structural Clean\n// Normalize company names, deduplicate by patent ID\n// Extract core fields\n\nconst raw = $input.first().json.rawResults || [];\n\nconst seen = new Set();\nconst cleaned = [];\n\nfor (const result of raw) {\n for (const patent of (result.patents || [])) {\n const id = patent.patent_id;\n if (!id || seen.has(id)) continue;\n seen.add(id);\n\n const title = (patent.patent_title || '').trim();\n if (!title) continue;\n\n // Parse filing date into quarter\n const date = new Date(patent.patent_date || '');\n const year = date.getFullYear();\n const quarter = Math.ceil((date.getMonth() + 1) / 3);\n const quarterLabel = `${year}-Q${quarter}`;\n\n // Extract inventors\n const inventors = (patent.inventors || []).map(inv => \n `${inv.inventor_first_name || ''} ${inv.inventor_last_name || ''}`.trim()\n ).filter(Boolean);\n\n // Extract CPC codes\n const cpcCodes = (patent.cpcs || []).map(c => c.cpc_subgroup_id).filter(Boolean);\n\n cleaned.push({\n patentId: id,\n company: result.company,\n title,\n abstract: (patent.patent_abstract || '').slice(0, 500),\n filingDate: patent.patent_date,\n quarterLabel,\n year,\n quarter,\n inventors,\n inventorCount: inventors.length,\n cpcCodes,\n assignee: patent.assignee_organization || result.alias\n });\n }\n}\n\nreturn [{ json: { patents: cleaned, totalCount: cleaned.length, fetchedAt: $input.first().json.fetchedAt } }];\n" }, "id": "node-1a", "name": "1A: Structural Clean", "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ -3920, 0 ] }, { "parameters": { "jsCode": "// Node 1B — Category Classifier + Velocity Pre-Scorer\n// Map CPC codes to readable categories\n// Calculate quarterly filing counts per company\n// Tag velocity zones\n\nconst { patents } = $input.first().json;\n\n// CPC to category mapping\nconst CPC_CATEGORIES = {\n 'G06N': 'AI/ML Algorithms',\n 'G06N3': 'Neural Networks',\n 'G06N3/063': 'AI Hardware',\n 'G06N20': 'Machine Learning',\n 'H01L': 'Semiconductor Devices',\n 'H01L29': 'Transistors',\n 'H01L21': 'Semiconductor Manufacturing',\n};\n\nconst categorized = patents.map(p => {\n const primaryCategory = p.cpcCodes.reduce((best, code) => {\n const match = Object.keys(CPC_CATEGORIES).find(k => code.startsWith(k));\n return match ? CPC_CATEGORIES[match] : best;\n }, 'General Technology');\n\n return { ...p, primaryCategory };\n});\n\n// Build quarterly filing counts per company\nconst quarterlyMap = {};\nfor (const patent of categorized) {\n const key = `${patent.company}::${patent.quarterLabel}`;\n if (!quarterlyMap[key]) {\n quarterlyMap[key] = {\n company: patent.company,\n quarter: patent.quarterLabel,\n year: patent.year,\n quarterNum: patent.quarter,\n count: 0,\n patents: [],\n inventors: new Set()\n };\n }\n quarterlyMap[key].count++;\n quarterlyMap[key].patents.push({ title: patent.title, abstract: patent.abstract });\n patent.inventors.forEach(inv => quarterlyMap[key].inventors.add(inv));\n}\n\n// Convert to array and calculate velocity\nconst companies = ['NVIDIA', 'AMD', 'Intel', 'Google', 'Apple'];\nconst quarterlyStats = [];\n\nfor (const company of companies) {\n const companyQuarters = Object.values(quarterlyMap)\n .filter(q => q.company === company)\n .sort((a, b) => a.year !== b.year ? a.year - b.year : a.quarterNum - b.quarterNum);\n\n for (let i = 0; i < companyQuarters.length; i++) {\n const current = companyQuarters[i];\n const prior = companyQuarters[i - 1];\n const priorYear = companyQuarters.find(\n q => q.year === current.year - 1 && q.quarterNum === current.quarterNum\n );\n\n const qoqChange = prior \n ? ((current.count - prior.count) / Math.max(prior.count, 1)) * 100 \n : 0;\n const yoyChange = priorYear \n ? ((current.count - priorYear.count) / Math.max(priorYear.count, 1)) * 100 \n : 0;\n\n // Velocity score 0-100 based on QoQ acceleration\n const velocityScore = Math.min(100, Math.max(0, Math.round(50 + qoqChange * 0.5)));\n\n // Zone classification\n const zone = qoqChange > 50 ? 'ACCELERATING' \n : qoqChange < -20 ? 'DECELERATING' \n : 'STEADY';\n\n quarterlyStats.push({\n company,\n quarter: current.quarter,\n year: current.year,\n quarterNum: current.quarterNum,\n filingCount: current.count,\n qoqChange: Math.round(qoqChange),\n yoyChange: Math.round(yoyChange),\n velocityScore,\n zone,\n uniqueInventors: current.inventors.size,\n patents: current.patents\n });\n }\n}\n\n// Get latest quarter stats per company for Claude analysis\nconst latestPerCompany = companies.map(company => {\n const quarters = quarterlyStats.filter(q => q.company === company);\n return quarters[quarters.length - 1] || null;\n}).filter(Boolean);\n\nreturn [{ \n json: { \n quarterlyStats, \n latestPerCompany,\n allPatents: categorized,\n timestamp: new Date().toISOString(),\n date: new Date().toISOString().split('T')[0]\n } \n}];\n" }, "id": "node-1b", "name": "1B: Category Classifier + Velocity Pre-Scorer", "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ -3680, 0 ] }, { "parameters": { "jsCode": "// Aggregate for Claude\n// Prepare structured inputs for 5 parallel Claude calls\n// Load previous quarter data from Supabase static data\n\nconst data = $input.first().json;\nconst { quarterlyStats, latestPerCompany, allPatents } = data;\n\n// Load previous concepts from static data\nconst staticData = $getWorkflowStaticData('global');\nconst previousConcepts = staticData.previousConcepts || {};\nconst previousInventors = staticData.previousInventors || {};\n\n// Prepare abstracts per company for Claude\nconst abstractsByCompany = {};\nfor (const company of ['NVIDIA', 'AMD', 'Intel', 'Google', 'Apple']) {\n const companyPatents = allPatents\n .filter(p => p.company === company)\n .slice(-20) // Last 20 patents\n .map(p => ({ title: p.title, abstract: p.abstract, quarter: p.quarterLabel }));\n abstractsByCompany[company] = companyPatents;\n}\n\n// Inventor lists per company\nconst inventorsByCompany = {};\nfor (const company of ['NVIDIA', 'AMD', 'Intel', 'Google', 'Apple']) {\n const inventors = [...new Set(\n allPatents\n .filter(p => p.company === company)\n .flatMap(p => p.inventors)\n )];\n inventorsByCompany[company] = inventors;\n}\n\nreturn [{\n json: {\n ...data,\n abstractsByCompany,\n inventorsByCompany,\n previousConcepts,\n previousInventors,\n acceleratingCompanies: latestPerCompany.filter(c => c.zone === 'ACCELERATING')\n }\n}];\n" }, "id": "aggregate-for-claude", "name": "Aggregate for Claude", "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ -3440, 0 ] }, { "parameters": { "promptType": "define", "text": "=You are a patent analytics expert specializing in semiconductor and AI hardware technology.\n\nAnalyze the patent filing velocity for these AI chip companies and score each one on acceleration.\n\nFor each company provide:\n- velocityScore (0-100): how aggressively are they filing?\n 0-30 = slowing down or dormant\n 31-60 = steady state\n 61-80 = notable acceleration\n 81-100 = aggressive expansion\n- trend: ACCELERATING / STEADY / DECELERATING\n- insight: one sentence on what the velocity pattern suggests\n\nReturn ONLY valid JSON array:\n[{ \"company\": string, \"velocityScore\": number, \"trend\": string, \"insight\": string }]\n\nData: {{ JSON.stringify($json.latestPerCompany.map(c => ({ company: c.company, currentQuarter: c.filingCount, qoqChange: c.qoqChange + '%', yoyChange: c.yoyChange + '%', zone: c.zone }))) }}", "messages": { "messageValues": [ { "message": "You are a patent analytics expert. Always respond with valid JSON only. No markdown, no explanation." } ] } }, "id": "claude-1-velocity", "name": "Claude 1: Velocity Score", "type": "@n8n/n8n-nodes-langchain.chainLlm", "typeVersion": 1.4, "position": [ -3200, -480 ] }, { "parameters": { "promptType": "define", "text": "=You are a technology intelligence analyst specializing in AI hardware patents.\n\nAnalyze these patent abstracts and identify NEW technical concepts that have NOT appeared in previous quarters.\n\nPrevious known concepts: {{ JSON.stringify($json.previousConcepts) }}\n\nFor each company, identify:\n- newConcepts: technical terms or approaches appearing for the first time\n- emergingThemes: 2-3 word themes that cluster multiple new concepts\n- noveltyScore (0-100): how novel is this quarter's technical vocabulary?\n\nReturn ONLY valid JSON:\n[{ \"company\": string, \"newConcepts\": string[], \"emergingThemes\": string[], \"noveltyScore\": number }]\n\nPatent abstracts by company: {{ JSON.stringify($json.abstractsByCompany) }}", "messages": { "messageValues": [ { "message": "You are a technology intelligence analyst. Always respond with valid JSON only. No markdown, no explanation." } ] } }, "id": "claude-2-concepts", "name": "Claude 2: Concept Novelty", "type": "@n8n/n8n-nodes-langchain.chainLlm", "typeVersion": 1.4, "position": [ -3200, -240 ] }, { "parameters": { "promptType": "define", "text": "=You are a talent intelligence analyst specializing in AI hardware research teams.\n\nAnalyze inventor lists for these companies and identify significant changes.\n\nPrevious known inventors: {{ JSON.stringify($json.previousInventors) }}\nCurrent inventors: {{ JSON.stringify($json.inventorsByCompany) }}\n\nFor each company identify:\n- newInventors: names appearing for first time\n- inventorGrowthRate: percentage change in unique inventors\n- teamExpansionSignal: EXPANDING / STABLE / CONTRACTING\n- insight: one sentence on what inventor changes suggest\n\nReturn ONLY valid JSON:\n[{ \"company\": string, \"newInventorCount\": number, \"teamExpansionSignal\": string, \"insight\": string }]\n", "messages": { "messageValues": [ { "message": "You are a talent intelligence analyst. Always respond with valid JSON only. No markdown, no explanation." } ] } }, "id": "claude-3-inventors", "name": "Claude 3: Inventor Network", "type": "@n8n/n8n-nodes-langchain.chainLlm", "typeVersion": 1.4, "position": [ -3200, 0 ] }, { "parameters": { "promptType": "define", "text": "=You are a competitive intelligence analyst specializing in semiconductor strategy.\n\nAnalyze cross-company patent patterns to detect convergence and divergence.\n\nIdentify:\n- convergenceTopics: technical areas where 3+ companies are filing simultaneously\n- divergenceTopics: areas where only 1 company is filing (potential differentiation)\n- leaderByCategory: which company leads in each technical sub-area\n- strategicInsight: 2 sentences on what the cross-company pattern suggests about the competitive landscape\n\nReturn ONLY valid JSON:\n{\n \"convergenceTopics\": string[],\n \"divergenceTopics\": [{ \"topic\": string, \"company\": string }],\n \"leaderByCategory\": [{ \"category\": string, \"leader\": string }],\n \"strategicInsight\": string\n}\n\nPatent data: {{ JSON.stringify($json.abstractsByCompany) }}", "messages": { "messageValues": [ { "message": "You are a competitive intelligence analyst. Always respond with valid JSON only. No markdown, no explanation." } ] } }, "id": "claude-4-convergence", "name": "Claude 4: Cross-Company Convergence", "type": "@n8n/n8n-nodes-langchain.chainLlm", "typeVersion": 1.4, "position": [ -3200, 240 ] }, { "parameters": { "promptType": "define", "text": "=You are a technology strategy analyst reading patent abstracts.\n\nClassify the strategic intent behind each company's current patent batch.\n\nChoose exactly one classification per company:\n- DEFENSIVE: protecting existing products, blocking competitors\n- EXPANSIVE: entering new adjacent markets\n- FOUNDATIONAL: platform-level bets, infrastructure patents\n- INCREMENTAL: improvements to existing products\n- EXPLORATORY: early-stage research, no clear commercial path yet\n\nReturn ONLY valid JSON:\n[{\n \"company\": string,\n \"intent\": string,\n \"confidence\": number,\n \"reasoning\": string,\n \"keyTechnicalThemes\": string[]\n}]\n\nPatent abstracts: {{ JSON.stringify($json.abstractsByCompany) }}", "messages": { "messageValues": [ { "message": "You are a technology strategy analyst. Always respond with valid JSON only. No markdown, no explanation." } ] } }, "id": "claude-5-intent", "name": "Claude 5: Strategic Intent", "type": "@n8n/n8n-nodes-langchain.chainLlm", "typeVersion": 1.4, "position": [ -3200, 480 ] }, { "parameters": { "model": { "__rl": true, "value": "REPLACE_WITH_RESOURCE", "mode": "list" }, "options": { "maxTokensToSample": 1500 } }, "id": "anthropic-model-1", "name": "Anthropic Model 1", "type": "@n8n/n8n-nodes-langchain.lmChatAnthropic", "typeVersion": 1.3, "position": [ -3200, -640 ] }, { "parameters": { "model": { "__rl": true, "value": "REPLACE_WITH_RESOURCE", "mode": "list" }, "options": { "maxTokensToSample": 1500 } }, "id": "anthropic-model-2", "name": "Anthropic Model 2", "type": "@n8n/n8n-nodes-langchain.lmChatAnthropic", "typeVersion": 1.3, "position": [ -3200, -400 ] }, { "parameters": { "model": { "__rl": true, "value": "REPLACE_WITH_RESOURCE", "mode": "list" }, "options": { "maxTokensToSample": 1500 } }, "id": "anthropic-model-3", "name": "Anthropic Model 3", "type": "@n8n/n8n-nodes-langchain.lmChatAnthropic", "typeVersion": 1.3, "position": [ -3200, -160 ] }, { "parameters": { "model": { "__rl": true, "value": "REPLACE_WITH_RESOURCE", "mode": "list" }, "options": { "maxTokensToSample": 1500 } }, "id": "anthropic-model-4", "name": "Anthropic Model 4", "type": "@n8n/n8n-nodes-langchain.lmChatAnthropic", "typeVersion": 1.3, "position": [ -3200, 80 ] }, { "parameters": { "model": { "__rl": true, "value": "REPLACE_WITH_RESOURCE", "mode": "list" }, "options": { "maxTokensToSample": 1500 } }, "id": "anthropic-model-5", "name": "Anthropic Model 5", "type": "@n8n/n8n-nodes-langchain.lmChatAnthropic", "typeVersion": 1.3, "position": [ -3200, 320 ] }, { "parameters": { "mode": "waitForAll", "numberInputs": 5 }, "id": "merge-claude-outputs", "name": "Merge Claude Outputs", "type": "n8n-nodes-base.merge", "typeVersion": 3, "position": [ -2960, 0 ] }, { "parameters": { "jsCode": "// Signal Aggregator\n// Parse all 5 Claude outputs and merge into single object\n\nfunction parseLlmOutput(text) {\n if (!text) return null;\n try {\n const clean = (text + '')\n .replace(/^```[\\w]*\\n?/m, '')\n .replace(/\\n?```$/m, '')\n .trim();\n return JSON.parse(clean);\n } catch (e) {\n return null;\n }\n}\n\nconst items = $input.all();\n\nlet velocityScores = null;\nlet conceptNovelty = null;\nlet inventorNetwork = null;\nlet convergence = null;\nlet strategicIntent = null;\n\nfor (const item of items) {\n const parsed = parseLlmOutput(item.json.text);\n if (!parsed) continue;\n\n if (Array.isArray(parsed) && parsed.length > 0) {\n const first = parsed[0];\n if ('velocityScore' in first && 'trend' in first) velocityScores = parsed;\n else if ('noveltyScore' in first) conceptNovelty = parsed;\n else if ('teamExpansionSignal' in first) inventorNetwork = parsed;\n else if ('intent' in first && 'keyTechnicalThemes' in first) strategicIntent = parsed;\n } else if (parsed && typeof parsed === 'object' && !Array.isArray(parsed)) {\n if ('convergenceTopics' in parsed) convergence = parsed;\n }\n}\n\nvelocityScores = velocityScores || [];\nconceptNovelty = conceptNovelty || [];\ninventorNetwork = inventorNetwork || [];\nconvergence = convergence || {};\nstrategicIntent = strategicIntent || [];\n\n// Get pipeline data from Aggregate for Claude node\nconst pipelineData = $('Aggregate for Claude').first().json;\n\n// Save current concepts and inventors to static data for next run comparison\nconst staticData = $getWorkflowStaticData('global');\nstaticData.previousConcepts = conceptNovelty.reduce((acc, c) => {\n acc[c.company] = c.newConcepts || [];\n return acc;\n}, {});\nstaticData.previousInventors = pipelineData.inventorsByCompany || {};\n\n// Build leaderboard\nconst leaderboard = (velocityScores || []).map(v => {\n const concept = (conceptNovelty || []).find(c => c.company === v.company) || {};\n const inventor = (inventorNetwork || []).find(i => i.company === v.company) || {};\n const intent = (strategicIntent || []).find(s => s.company === v.company) || {};\n const quarterly = (pipelineData.latestPerCompany || []).find(q => q.company === v.company) || {};\n\n return {\n company: v.company,\n velocityScore: v.velocityScore,\n trend: v.trend,\n velocityInsight: v.insight,\n filingCount: quarterly.filingCount || 0,\n qoqChange: quarterly.qoqChange || 0,\n yoyChange: quarterly.yoyChange || 0,\n noveltyScore: concept.noveltyScore || 0,\n newConcepts: concept.newConcepts || [],\n emergingThemes: concept.emergingThemes || [],\n teamExpansionSignal: inventor.teamExpansionSignal || 'UNKNOWN',\n newInventorCount: inventor.newInventorCount || 0,\n inventorInsight: inventor.insight || '',\n strategicIntent: intent.intent || 'UNKNOWN',\n intentConfidence: intent.confidence || 0,\n intentReasoning: intent.reasoning || '',\n keyTechnicalThemes: intent.keyTechnicalThemes || []\n };\n}).sort((a, b) => b.velocityScore - a.velocityScore);\n\nreturn [{\n json: {\n leaderboard,\n convergence,\n quarterlyStats: pipelineData.quarterlyStats,\n timestamp: pipelineData.timestamp,\n date: pipelineData.date,\n totalPatentsAnalyzed: (pipelineData.allPatents || []).length\n }\n}];\n" }, "id": "signal-aggregator", "name": "Signal Aggregator", "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ -2720, 0 ] }, { "parameters": { "method": "POST", "url": "YOUR_SUPABASE_URL/rest/v1/patent_runs", "sendHeaders": true, "headerParameters": { "parameters": [ { "name": "apikey", "value": "REPLACE_WITH_APIKEY" }, { "name": "Authorization", "value": "REPLACE_WITH_AUTHORIZATION" }, { "name": "Content-Type", "value": "application/json" }, { "name": "Prefer", "value": "return=minimal" } ] }, "sendBody": true, "bodyParameters": { "parameters": [ { "name": "date", "value": "={{ $json.date }}" }, { "name": "timestamp", "value": "={{ $json.timestamp }}" }, { "name": "leaderboard", "value": "={{ $json.leaderboard }}" }, { "name": "convergence", "value": "={{ $json.convergence }}" }, { "name": "quarterly_stats", "value": "={{ $json.quarterlyStats }}" }, { "name": "total_patents_analyzed", "value": "={{ $json.totalPatentsAnalyzed }}" } ] }, "options": {} }, "id": "insert-to-supabase", "name": "Insert to Supabase", "type": "n8n-nodes-base.httpRequest", "typeVersion": 4.2, "position": [ -2480, 0 ] }, { "parameters": { "jsCode": "// Check if triggered by webhook or schedule\n// Only respond if webhook-triggered\nconst mode = $execution.mode;\nreturn [{ json: { ...$input.first().json, triggeredByWebhook: mode === 'webhook' } }];\n" }, "id": "check-trigger", "name": "Check Trigger Type", "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ -2240, 0 ] }, { "parameters": { "conditions": { "options": { "caseSensitive": true }, "conditions": [ { "id": "webhook-check", "leftValue": "={{ $json.triggeredByWebhook }}", "rightValue": true, "operator": { "type": "boolean", "operation": "true" } } ] } }, "id": "if-webhook", "name": "If Webhook", "type": "n8n-nodes-base.if", "typeVersion": 2, "position": [ -2000, 0 ] }, { "parameters": { "respondWith": "json", "responseBody": "={{ JSON.stringify({ status: 'success', message: 'Pipeline completed', date: $json.date, totalPatents: $json.totalPatentsAnalyzed, topCompany: $json.leaderboard[0]?.company, topVelocityScore: $json.leaderboard[0]?.velocityScore }) }}", "options": { "responseHeaders": { "values": [ { "name": "Content-Type", "value": "application/json" }, { "name": "Access-Control-Allow-Origin", "value": "*" } ] } } }, "id": "pipeline-response", "name": "Pipeline Response", "type": "n8n-nodes-base.respondToWebhook", "typeVersion": 1.1, "position": [ -1760, -160 ] }, { "parameters": { "jsCode": "// Build Dashboard HTML\n// Embed full dashboard as string — no fs required\nconst html = `\n\n\n \n \n Patent Filing Velocity Tracker\n \n \n\n\n

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Patent Filing Velocity Tracker

AI Chips · NVIDIA · AMD · Intel · Google · Apple

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Velocity Leaderboard
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Strategic Intent
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Cross-Company Convergence
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Filing Velocity Over Time
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Emerging Concepts by Company
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\n \n\n`;\n\nreturn [{ json: { html } }];\n" }, "id": "build-dashboard", "name": "Build Dashboard HTML", "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ -2480, 240 ] }, { "parameters": { "respondWith": "text", "responseBody": "={{ $json.html }}", "options": { "responseHeaders": { "values": [ { "name": "Content-Type", "value": "text/html; charset=utf-8" } ] } } }, "id": "serve-dashboard", "name": "Serve Dashboard HTML", "type": "n8n-nodes-base.respondToWebhook", "typeVersion": 1.1, "position": [ -2240, 240 ] }, { "id": "a87d5b36-7c1c-53f0-b9a1-8d45ac962d4c", "name": "Publication · Overview and setup", "type": "n8n-nodes-base.stickyNote", "typeVersion": 1, "position": [ -5200, -640 ], "parameters": { "content": "# Patent Filing Velocity Tracker\n\n## Purpose and structure\nThis folder contains the **Patent Filing Velocity Tracker** workflow. Its executable nodes use `chainLlm`, `code`, `httpRequest`, `if`, `lmChatAnthropic`, `merge`, `respondToWebhook`, `webhook`. The table and connection map below are derived from the JSON, not an inferred guarantee of behavior.\n\n## Setup\nImport inactive. Configure your own credentials and replace REPLACE_WITH_* values. Review external destinations and Code nodes before running.\n\n## Entry points\nManual Run Trigger, Dashboard Webhook\n\n## Verification\nSanitized source candidate; not runtime-tested. This overview is generated from node metadata. Read the folder README for the connection map, credential types, and license.\n\n## Attribution\nNik Bear Brown; rights confirmed 2026-10-19\nMIT; preserve source notices.", "width": 700, "height": 800, "color": 1 } } ], "connections": { "Manual Run Trigger": { "main": [ [ { "node": "Fetch Patent Data", "type": "main", "index": 0 } ] ] }, "Dashboard Webhook": { "main": [ [ { "node": "Build Dashboard HTML", "type": "main", "index": 0 } ] ] }, "Fetch Patent Data": { "main": [ [ { "node": "1A: Structural Clean", "type": "main", "index": 0 } ] ] }, "1A: Structural Clean": { "main": [ [ { "node": "1B: Category Classifier + Velocity Pre-Scorer", "type": "main", "index": 0 } ] ] }, "1B: Category Classifier + Velocity Pre-Scorer": { "main": [ [ { "node": "Aggregate for Claude", "type": "main", "index": 0 } ] ] }, "Aggregate for Claude": { "main": [ [ { "node": "Claude 1: Velocity Score", "type": "main", "index": 0 }, { "node": "Claude 2: Concept Novelty", "type": "main", "index": 0 }, { "node": "Claude 3: Inventor Network", "type": "main", "index": 0 }, { "node": "Claude 4: Cross-Company Convergence", "type": "main", "index": 0 }, { "node": "Claude 5: Strategic Intent", "type": "main", "index": 0 } ] ] }, "Claude 1: Velocity Score": { "main": [ [ { "node": "Merge Claude Outputs", "type": "main", "index": 0 } ] ] }, "Claude 2: Concept Novelty": { "main": [ [ { "node": "Merge Claude Outputs", "type": "main", "index": 1 } ] ] }, "Claude 3: Inventor Network": { "main": [ [ { "node": "Merge Claude Outputs", "type": "main", "index": 2 } ] ] }, "Claude 4: Cross-Company Convergence": { "main": [ [ { "node": "Merge Claude Outputs", "type": "main", "index": 3 } ] ] }, "Claude 5: Strategic Intent": { "main": [ [ { "node": "Merge Claude Outputs", "type": "main", "index": 4 } ] ] }, "Merge Claude Outputs": { "main": [ [ { "node": "Signal Aggregator", "type": "main", "index": 0 } ] ] }, "Signal Aggregator": { "main": [ [ { "node": "Insert to Supabase", "type": "main", "index": 0 } ] ] }, "Insert to Supabase": { "main": [ [ { "node": "Check Trigger Type", "type": "main", "index": 0 } ] ] }, "Check Trigger Type": { "main": [ [ { "node": "If Webhook", "type": "main", "index": 0 } ] ] }, "If Webhook": { "main": [ [ { "node": "Pipeline Response", "type": "main", "index": 0 } ], [] ] }, "Build Dashboard HTML": { "main": [ [ { "node": "Serve Dashboard HTML", "type": "main", "index": 0 } ] ] }, "Anthropic Model 1": { "ai_languageModel": [ [ { "node": "Claude 1: Velocity Score", "type": "ai_languageModel", "index": 0 } ] ] }, "Anthropic Model 2": { "ai_languageModel": [ [ { "node": "Claude 2: Concept Novelty", "type": "ai_languageModel", "index": 0 } ] ] }, "Anthropic Model 3": { "ai_languageModel": [ [ { "node": "Claude 3: Inventor Network", "type": "ai_languageModel", "index": 0 } ] ] }, "Anthropic Model 4": { "ai_languageModel": [ [ { "node": "Claude 4: Cross-Company Convergence", "type": "ai_languageModel", "index": 0 } ] ] }, "Anthropic Model 5": { "ai_languageModel": [ [ { "node": "Claude 5: Strategic Intent", "type": "ai_languageModel", "index": 0 } ] ] } }, "active": false, "settings": { "executionOrder": "v1" } }