[{"_1":2,"_3":-5,"_4":-5},"loaderData",{"_5":6,"_7":8,"_9":10},"actionData","errors","root",{"_264":265,"_266":267},"routes/_app.x.$handle.$name",{"_11":12,"_13":14,"_15":-7,"_18":19,"_17":-7,"_199":-5,"_20":200,"_22":201,"_202":203,"_204":205,"_26":206,"_24":207,"_208":-5,"_209":-5,"_210":51,"_211":212,"_213":43,"_214":-5,"_215":-5,"_216":217},"routes/_app.x.$handle.$name.code.$",{"_11":12,"_13":14,"_15":16,"_17":-7,"_18":19,"_20":21,"_22":23,"_24":25,"_26":27,"_28":-5,"_29":-5,"_30":-5,"_31":-5,"_32":-5},"handle","QBench","name","hubspot-contacts","branchName","main","version","path","dashboard.html","project",{"_33":143,"_13":14,"_44":144,"_145":-5,"_146":51,"_147":148,"_149":148,"_150":151,"_152":-5,"_153":154,"_155":61,"_156":43,"_157":-5,"_158":-5,"_159":74,"_160":161,"_162":163,"_164":165,"_166":167,"_168":-5,"_169":170,"_171":170,"_172":173,"_174":173,"_175":173,"_176":170,"_177":170,"_178":179,"_180":181,"_182":183,"_184":51},"tree",[54,55,56,57,58],"file",{"_33":34,"_13":19,"_35":36,"_37":-5,"_38":39,"_40":41,"_42":43,"_44":45,"_17":46,"_47":24,"_48":49,"_50":51,"_52":-5,"_18":53},"contents",[],"upstream","pull","ahead","behind","envVars","id","5f524420-5a2e-11f1-b7fd-ee650bb23af1","fileId","dfdbe284-59f4-11f1-ba23-ee650bb23af1","parentId","branchId","481c08c8-4fab-11f1-9071-ee650bb23af1","branchVersion",15,"latest",true,"createdAt",["D",1779929063931],1,"fileType","content","\n\n\n \n \n HubSpot CRM Dashboard\n \n \n\n\n

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HubSpot CRM Dashboard

\n \n \n Enrichment Review\n \n \n View Source\n \n

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\n\n \n \n\n\n","deleted",false,"label",[19],{"_33":90,"_13":91,"_35":92,"_37":-5,"_38":39,"_40":93,"_42":43,"_44":94,"_17":74,"_47":95,"_48":-5,"_50":51,"_52":-5,"_67":96,"_18":97},{"_33":34,"_13":19,"_35":36,"_37":-5,"_38":39,"_40":41,"_42":43,"_44":87,"_17":46,"_47":24,"_48":49,"_50":51,"_52":-5,"_67":88,"_18":89},{"_33":79,"_13":80,"_35":81,"_37":-5,"_38":39,"_40":82,"_42":43,"_44":83,"_17":74,"_47":24,"_48":84,"_50":51,"_52":-5,"_67":85,"_18":86},{"_33":70,"_13":71,"_35":72,"_37":-5,"_38":39,"_40":64,"_42":43,"_44":73,"_17":74,"_47":75,"_48":76,"_50":51,"_52":-5,"_67":77,"_18":78},{"_33":59,"_13":60,"_35":61,"_37":-5,"_38":39,"_40":62,"_42":43,"_44":63,"_17":64,"_47":65,"_48":66,"_50":51,"_52":-5,"_67":68,"_18":69},"26c16bcc-5a2e-11f1-9429-ee650bb23af1","main.ts","5b8a1030-4fab-11f1-8892-ee650bb23af1",13,["D",1779928969029],4,"http","import { parseVal, serveFile } from \"https://esm.town/v/std/utils/index.ts\";\nimport { fetchContacts, fetchDeals, fetchCompanies, hasToken } from \"./hubspot.ts\";\nimport {\n initDB,\n getClassifications,\n getStats,\n updateReviewStatus,\n bulkUpdateReviewStatus,\n getLatestRun,\n} from \"./enrichment/db.ts\";\nimport { runPipeline } from \"./enrichment/pipeline.ts\";\n\nasync function handleApiRequest(fetcher: () => Promise) {\n try {\n const data = await fetcher();\n if (!data) return Response.json({ error: \"no_token\" }, { status: 401 });\n return Response.json(data);\n } catch (e: any) {\n return Response.json({ error: e.message }, { status: 500 });\n }\n}\n\nexport default async function(req: Request): Promise {\n const url = new URL(req.url);\n\n if (url.pathname === \"/source\") {\n return new Response(null, { status: 302, headers: { Location: parseVal().links.self.val } });\n }\n\n // ── Original CRM dashboard routes ──────────────────────────────\n if (url.pathname === \"/api/contacts\") return handleApiRequest(fetchContacts);\n if (url.pathname === \"/api/deals\") return handleApiRequest(fetchDeals);\n if (url.pathname === \"/api/companies\") return handleApiRequest(fetchCompanies);\n\n // ── Enrichment pipeline routes ─────────────────────────────────\n\n // Initialize DB (idempotent)\n if (url.pathname.startsWith(\"/api/enrichment\")) {\n await initDB();\n }\n\n // Start a pipeline run\n if (url.pathname === \"/api/enrichment/run\" && req.method === \"POST\") {\n const body = await req.json().catch(() => ({}));\n const maxCompanies = body.maxCompanies || 5; // Default to 5 for safety\n const dryRun = body.dryRun || false;\n\n // Fire-and-forget — respond immediately, process in background\n const responsePromise = runPipeline({\n maxCompanies,\n dryRun,\n delayBetweenMs: 2000,\n });\n\n // Don't await — let it run in background\n responsePromise.catch((err) => console.error(\"Pipeline error:\", err));\n\n return Response.json({\n status: \"started\",\n message: `Processing up to ${maxCompanies} companies${dryRun ? \" (DRY RUN)\" : \"\"}`,\n });\n }\n\n // Get pipeline status / latest run\n if (url.pathname === \"/api/enrichment/status\") {\n const run = await getLatestRun();\n const stats = await getStats();\n return Response.json({ run, stats });\n }\n\n // Get classifications (with filters)\n if (url.pathname === \"/api/enrichment/classifications\") {\n const status = url.searchParams.get(\"status\") || undefined;\n const icpFitTier = url.searchParams.get(\"icp\") || undefined;\n const minConfidence = url.searchParams.get(\"minConfidence\")\n ? parseInt(url.searchParams.get(\"minConfidence\")!)\n : undefined;\n const limit = parseInt(url.searchParams.get(\"limit\") || \"50\");\n const offset = parseInt(url.searchParams.get(\"offset\") || \"0\");\n\n const data = await getClassifications({ status, icpFitTier, minConfidence, limit, offset });\n return Response.json(data);\n }\n\n // Review a single classification\n if (url.pathname === \"/api/enrichment/review\" && req.method === \"POST\") {\n const body = await req.json();\n await updateReviewStatus(body.hubspotId, body.status, body.notes);\n return Response.json({ ok: true });\n }\n\n // Bulk review\n if (url.pathname === \"/api/enrichment/bulk-review\" && req.method === \"POST\") {\n const body = await req.json();\n await bulkUpdateReviewStatus(body.hubspotIds, body.status);\n return Response.json({ ok: true, count: body.hubspotIds.length });\n }\n\n // ── Page routing ───────────────────────────────────────────────\n if (url.pathname === \"/enrichment\") {\n return serveFile(\"./enrichment-dashboard.html\", import.meta.url);\n }\n\n return serveFile(\"./dashboard.html\", import.meta.url);\n}\n","children",[],[60],"cc95e79c-59f4-11f1-b759-ee650bb23af1","hubspot.ts","cc95e850-59f4-11f1-b759-ee650bb23af1",["D",1779904336432],0,"script","const TOKEN = Deno.env.get(\"TOKEN\") || \"\";\n\nconst HEADERS = {\n Authorization: `Bearer ${TOKEN}`,\n \"Content-Type\": \"application/json\",\n};\n\nexport function hasToken() {\n return !!TOKEN;\n}\n\nasync function fetchObjects(objectType: string, properties: string[], limit = 100) {\n if (!TOKEN) return null;\n const props = properties.join(\",\");\n const res = await fetch(\n `https://api.hubapi.com/crm/v3/objects/${objectType}?limit=${limit}&properties=${props}`,\n { headers: HEADERS },\n );\n if (!res.ok) {\n const err = await res.text();\n throw new Error(`HubSpot API error (${res.status}): ${err}`);\n }\n return res.json();\n}\n\nexport function fetchContacts() {\n return fetchObjects(\"contacts\", [\n \"firstname\", \"lastname\", \"email\", \"phone\", \"company\", \"lifecyclestage\", \"createdate\",\n ]);\n}\n\nexport function fetchDeals() {\n return fetchObjects(\"deals\", [\n \"dealname\", \"amount\", \"dealstage\", \"pipeline\", \"closedate\", \"createdate\", \"hubspot_owner_id\",\n ]);\n}\n\nexport function fetchCompanies() {\n return fetchObjects(\"companies\", [\n \"name\", \"domain\", \"industry\", \"numberofemployees\", \"city\", \"state\", \"country\", \"createdate\",\n ]);\n}\n",[],[71],"55859dd4-5a2e-11f1-a59a-ee650bb23af1","enrichment-dashboard.html","55859eb0-5a2e-11f1-a59a-ee650bb23af1",14,["D",1779929047493],"\n\n\n \n \n QBench — Account Enrichment Review\n \n \n\n\n

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Account Enrichment Review

AI-classified industry taxonomy — review before pushing to HubSpot

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	Company	Current Industry	Tier 1	Tier 2	Tier 3 (Niche)	ICP	Segment	Conf	Status	Actions
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\n\n \n \n\n\n",[],[80],["D",1779929063931],[],[19],"9c18a184-5a2d-11f1-822b-ee650bb23af1","enrichment","9c18a224-5a2d-11f1-822b-ee650bb23af1",7,["D",1779928736398],"directory",[98,99,100,101,102],[91],{"_33":135,"_13":136,"_35":137,"_37":92,"_38":39,"_40":138,"_42":43,"_44":139,"_17":74,"_47":75,"_48":140,"_50":51,"_52":-5,"_67":141,"_18":142},{"_33":127,"_13":128,"_35":129,"_37":92,"_38":39,"_40":130,"_42":43,"_44":131,"_17":74,"_47":75,"_48":132,"_50":51,"_52":-5,"_67":133,"_18":134},{"_33":119,"_13":120,"_35":121,"_37":92,"_38":39,"_40":122,"_42":43,"_44":123,"_17":74,"_47":75,"_48":124,"_50":51,"_52":-5,"_67":125,"_18":126},{"_33":111,"_13":112,"_35":113,"_37":92,"_38":39,"_40":114,"_42":43,"_44":115,"_17":74,"_47":75,"_48":116,"_50":51,"_52":-5,"_67":117,"_18":118},{"_33":103,"_13":104,"_35":105,"_37":92,"_38":39,"_40":106,"_42":43,"_44":107,"_17":74,"_47":75,"_48":108,"_50":51,"_52":-5,"_67":109,"_18":110},"f12c16ba-5a2d-11f1-83ca-ee650bb23af1","web-search.ts","f12c1778-5a2d-11f1-83ca-ee650bb23af1",10,["D",1779928879136],"/**\n * Web Search Enrichment — fetches publicly available info about a company\n * to provide context for the AI classifier.\n *\n * Strategy:\n * 1. If domain exists, fetch the homepage and extract a description\n * 2. Search for \"{company name} + lab/testing/manufacturing\" for context\n */\n\nexport interface WebEnrichmentResult {\n context: string;\n sources: string[];\n}\n\n/**\n * Enrich a company by fetching its website and searching for context.\n * Returns a text summary suitable for the LLM classifier.\n */\nexport async function enrichCompany(\n name: string,\n domain: string | null,\n): Promise {\n const parts: string[] = [];\n const sources: string[] = [];\n\n // 1. Try fetching the company homepage\n if (domain) {\n try {\n const url = domain.startsWith(\"http\") ? domain : `https://${domain}`;\n const res = await fetch(url, {\n headers: { \"User-Agent\": \"QBench-Enrichment/1.0\" },\n signal: AbortSignal.timeout(8000),\n redirect: \"follow\",\n });\n if (res.ok) {\n const html = await res.text();\n const extracted = extractPageInfo(html);\n if (extracted) {\n parts.push(`[Website (${domain})]: ${extracted}`);\n sources.push(url);\n }\n }\n } catch {\n // Domain fetch failed — that's fine, we'll rely on search\n }\n }\n\n // 2. Web search for company context\n try {\n const searchQuery = buildSearchQuery(name, domain);\n const searchResult = await webSearch(searchQuery);\n if (searchResult) {\n parts.push(`[Search]: ${searchResult}`);\n sources.push(`search: \"${searchQuery}\"`);\n }\n } catch {\n // Search failed — classifier will work with whatever we have\n }\n\n return {\n context: parts.join(\"\\n\\n\") || \"No web enrichment data available.\",\n sources,\n };\n}\n\nfunction buildSearchQuery(name: string, domain: string | null): string {\n // Clean company name for search\n const cleanName = name.replace(/[,.\\-()]/g, \" \").replace(/\\s+/g, \" \").trim();\n // Limit to first 4 words to keep search focused\n const shortName = cleanName.split(\" \").slice(0, 4).join(\" \");\n return `${shortName} laboratory testing manufacturing`;\n}\n\n/**\n * Simple web search using a public search API.\n * Falls back gracefully if unavailable.\n */\nasync function webSearch(query: string): Promise {\n try {\n // Use DuckDuckGo instant answer API (no key required)\n const encoded = encodeURIComponent(query);\n const res = await fetch(\n `https://api.duckduckgo.com/?q=${encoded}&format=json&no_html=1&skip_disambig=1`,\n { signal: AbortSignal.timeout(5000) },\n );\n if (!res.ok) return null;\n const data = await res.json();\n\n const parts: string[] = [];\n if (data.Abstract) parts.push(data.Abstract);\n if (data.RelatedTopics?.length) {\n const topics = data.RelatedTopics\n .slice(0, 3)\n .map((t: any) => t.Text)\n .filter(Boolean);\n if (topics.length) parts.push(topics.join(\". \"));\n }\n return parts.join(\" \") || null;\n } catch {\n return null;\n }\n}\n\n/**\n * Extract useful text from an HTML page — title, meta description,\n * and first meaningful text content.\n */\nfunction extractPageInfo(html: string): string | null {\n const parts: string[] = [];\n\n // Title\n const titleMatch = html.match(/]*>(.*?)<\\/title>/si);\n if (titleMatch) parts.push(`Title: ${cleanText(titleMatch[1])}`);\n\n // Meta description\n const metaMatch = html.match(\n /]+name=[\"']description[\"'][^>]+content=[\"']([^\"']+)[\"']/si,\n );\n if (metaMatch) parts.push(`Description: ${cleanText(metaMatch[1])}`);\n\n // OG description as fallback\n if (!metaMatch) {\n const ogMatch = html.match(\n /]+property=[\"']og:description[\"'][^>]+content=[\"']([^\"']+)[\"']/si,\n );\n if (ogMatch) parts.push(`Description: ${cleanText(ogMatch[1])}`);\n }\n\n // Extract first ~500 chars of visible body text\n const bodyMatch = html.match(/]*>([\\s\\S]*?)<\\/body>/si);\n if (bodyMatch) {\n const stripped = bodyMatch[1]\n .replace(//gi, \"\")\n .replace(//gi, \"\")\n .replace(//gi, \"\")\n .replace(//gi, \"\")\n .replace(//gi, \"\")\n .replace(/<[^>]+>/g, \" \")\n .replace(/\\s+/g, \" \")\n .trim();\n if (stripped.length > 50) {\n parts.push(`Content: ${stripped.slice(0, 500)}`);\n }\n }\n\n return parts.length > 0 ? parts.join(\". \") : null;\n}\n\nfunction cleanText(text: string): string {\n return text\n .replace(/&/g, \"&\")\n .replace(/</g, \"<\")\n .replace(/>/g, \">\")\n .replace(/&#?\\w+;/g, \" \")\n .replace(/\\s+/g, \" \")\n .trim();\n}\n",[],[91,104],"cc04dcbe-5a2d-11f1-af29-ee650bb23af1","taxonomy.ts","cc04ddae-5a2d-11f1-af29-ee650bb23af1",8,["D",1779928816802],"/**\n * QBench Industry Taxonomy v4.4\n * Encodes the full 3-tier industry hierarchy, ICP fit, segment rules,\n * lab operation types, and regulatory frameworks.\n *\n * DETERMINISTIC RULES are enforced here — the LLM only picks Tier 2 + Tier 3.\n * Everything else (Tier 1, ICP, Segment) is derived from lookups.\n */\n\n// ── Tier 2 → Tier 1 lookup (deterministic, never set by LLM) ──────────\nexport const TIER2_TO_TIER1: Record = {\n \"Therapeutic Development\": \"Life Sciences\",\n \"Contract Research & Manufacturing\": \"Life Sciences\",\n \"Life Science Tools & Platforms\": \"Life Sciences\",\n \"Precision Medicine & Diagnostics\": \"Life Sciences\",\n \"Food & Beverage Manufacturing\": \"Food & Beverage\",\n \"Contract Food & Beverage Testing\": \"Food & Beverage\",\n \"Health Supplements\": \"Food & Beverage\",\n \"Agriculture\": \"Agriculture\",\n \"Chemicals & Materials\": \"Manufacturing\",\n \"Metals, Minerals & Construction\": \"Manufacturing\",\n \"Engineered Products\": \"Manufacturing\",\n \"Packaging & Paper\": \"Manufacturing\",\n \"Contract Engineering & Analytical\": \"Manufacturing\",\n \"Consumer Goods\": \"Manufacturing\",\n \"Personal Care Products\": \"Manufacturing\",\n \"Oil, Gas & Petrochemical\": \"Energy & Natural Resources\",\n \"Power & Utilities\": \"Energy & Natural Resources\",\n \"Clean Energy & Storage\": \"Energy & Natural Resources\",\n \"Environmental Testing\": \"Environmental & Compliance Testing\",\n \"Product Safety & Compliance\": \"Environmental & Compliance Testing\",\n \"Cannabis & Hemp Testing\": \"Cannabis & Hemp Testing\",\n \"Electronics & Semiconductor\": \"Electronics & Semiconductor\",\n \"Independent Clinical\": \"Healthcare\",\n \"Veterinary Diagnostics\": \"Healthcare\",\n \"Hospital & Health System\": \"Healthcare\",\n \"University Research\": \"Academic & Government Research\",\n \"Government & National Research\": \"Academic & Government Research\",\n \"Forensic & Public Safety\": \"Forensic & Public Safety\",\n};\n\n// ── Tier 3 → ICP Fit lookup (deterministic, overrides mid-tier ICP) ────\nexport type ICPFitTier = \"Bullseye\" | \"Ring 1\" | \"Ring 2\" | \"Not Target\";\n\nexport const TIER3_TO_ICP: Record = {\n // Life Sciences\n \"Therapeutic Biotech (Preclinical–Phase II)\": \"Bullseye\",\n \"Pharma R&D & QC\": \"Ring 1\",\n \"Preclinical / Discovery CROs\": \"Bullseye\",\n \"Bioanalytical / GLP CROs (DMPK, PK/PD)\": \"Bullseye\",\n \"CDMOs\": \"Bullseye\",\n \"Platform/Tools Biotech\": \"Bullseye\",\n \"Molecular and Genetic Specialty\": \"Ring 1\",\n \"Infectious Disease\": \"Ring 1\",\n \"Cancer Diagnostic\": \"Ring 1\",\n // Food & Beverage\n \"Meat, Poultry & Seafood Processing\": \"Ring 1\",\n \"Dairy Processing\": \"Ring 1\",\n \"Beverage Production (Breweries, Wineries, Distilleries)\": \"Ring 1\",\n \"Bakery, Snacks & Confectionery\": \"Ring 1\",\n \"Fruit & Vegetable Processing\": \"Ring 1\",\n \"Ingredients, Flavors & Additives\": \"Ring 1\",\n \"Pet Food & Animal Food Manufacturing\": \"Ring 2\",\n \"Tobacco Manufacturing\": \"Not Target\",\n \"Contract Food Testing\": \"Ring 1\",\n \"Nutraceuticals\": \"Bullseye\",\n \"Health Supplements\": \"Bullseye\",\n \"Vitamins\": \"Bullseye\",\n // Agriculture\n \"Seed & Trait R&D\": \"Ring 2\",\n \"Soil Testing Services\": \"Ring 2\",\n \"Plant Pathology & Diagnostics\": \"Ring 2\",\n \"Public Agricultural Research\": \"Not Target\",\n \"Ag Biotech Startups (Biofertilizers, Biocontrol)\": \"Ring 2\",\n // Manufacturing — Chemicals & Materials\n \"Specialty Chemicals\": \"Bullseye\",\n \"Basic & Commodity Chemicals\": \"Ring 1\",\n \"Polymers, Resins & Plastics\": \"Bullseye\",\n \"Coatings, Paints & Adhesives\": \"Bullseye\",\n \"Fertilizers & Agrochemical Manufacturing\": \"Ring 2\",\n // Manufacturing — Metals, Minerals & Construction\n \"Metals & Metallurgy (Primary + Fabricated)\": \"Bullseye\",\n \"Mining & Mineral Processing\": \"Ring 2\",\n \"Battery & Rare-Earth Minerals Processing\": \"Ring 2\",\n \"Building Materials (Cement, Glass, Ceramics)\": \"Bullseye\",\n \"Engineered Wood & Lumber\": \"Ring 2\",\n \"Construction & Geotechnical Testing\": \"Ring 2\",\n // Manufacturing — Engineered Products\n \"Automotive & EV (OEMs + Suppliers)\": \"Bullseye\",\n \"Aerospace & Defense Manufacturing\": \"Bullseye\",\n \"Medical Devices & Diagnostics Manufacturing\": \"Bullseye\",\n \"Industrial Machinery & Instrumentation\": \"Ring 2\",\n \"Plastics & Rubber Products\": \"Bullseye\",\n \"Appliances & Home Equipment\": \"Bullseye\",\n // Manufacturing — Packaging & Paper\n \"Mills & Converters\": \"Ring 2\",\n // Manufacturing — Contract Engineering & Analytical\n \"Contract Physical & Engineering R&D\": \"Ring 1\",\n // Manufacturing — Consumer Goods\n \"Household Cleaning & Chemical Products\": \"Bullseye\",\n \"Contract Manufacturers (CPG)\": \"Bullseye\",\n \"Apparel, Footwear & Textiles\": \"Ring 2\",\n \"Sports & Recreation Equipment\": \"Ring 2\",\n \"Furniture\": \"Not Target\",\n // Manufacturing — Personal Care Products\n \"Cosmetics & Personal Care\": \"Bullseye\",\n \"Fragrance & Flavor Houses\": \"Bullseye\",\n // Energy & Natural Resources\n \"Refinery QC\": \"Bullseye\",\n \"Upstream Core Analysis & Reservoir Fluids\": \"Bullseye\",\n \"Petrochemical Process\": \"Bullseye\",\n \"Fuel & Lubricant Analysis Services\": \"Bullseye\",\n \"Power Plants\": \"Bullseye\",\n \"Water & Wastewater Utility\": \"Bullseye\",\n \"Energy Storage & Battery R&D\": \"Bullseye\",\n \"Renewable Energy\": \"Bullseye\",\n // Environmental & Compliance Testing\n \"Water & Wastewater Testing\": \"Ring 2\",\n \"Soil & Groundwater Testing\": \"Ring 2\",\n \"Air & Emissions Testing\": \"Ring 2\",\n \"Industrial Hygiene & Occupational Health\": \"Ring 2\",\n \"Ecology & Radiochemistry\": \"Not Target\",\n \"EMC / Compliance (NRTL & 3rd-Party)\": \"Ring 2\",\n \"Consumer Product Safety & Claims\": \"Ring 2\",\n // Cannabis & Hemp Testing\n \"Cannabis Compliance Testing\": \"Not Target\",\n \"Hemp / CBD Testing\": \"Not Target\",\n // Electronics & Semiconductor\n \"Front-End Fabs\": \"Ring 2\",\n \"OSAT / Test & Packaging\": \"Ring 2\",\n \"Device OEM R&D\": \"Ring 2\",\n \"PCB Assembly QA\": \"Ring 2\",\n // Healthcare (all Not Target)\n \"Regional Reference Labs\": \"Not Target\",\n \"Pathology / Anatomic Pathology Groups\": \"Not Target\",\n \"Toxicology & Drug Testing\": \"Not Target\",\n \"Fertility & Reproductive Medicine\": \"Not Target\",\n \"National Reference\": \"Not Target\",\n \"Private Vet Diagnostic\": \"Not Target\",\n \"Public Vet Diagnostic (AAVLD)\": \"Not Target\",\n \"Aquaculture Diagnostic\": \"Not Target\",\n \"Community Hospital\": \"Not Target\",\n \"Academic Medical Center\": \"Not Target\",\n \"Physician Office (POL)\": \"Not Target\",\n \"Outpatient Clinics\": \"Not Target\",\n \"Retail Clinic / Pharmacy\": \"Not Target\",\n \"Dialysis & Specialty Clinic\": \"Not Target\",\n // Academic & Government Research (all Not Target)\n \"R1 Biomedical Research\": \"Not Target\",\n \"R1 Engineering & Materials\": \"Not Target\",\n \"R2 / Other University Research\": \"Not Target\",\n \"University Core Facilities\": \"Not Target\",\n \"Federal National Research\": \"Not Target\",\n // Forensic & Public Safety (all Not Target)\n \"Public Crime\": \"Not Target\",\n \"Private Forensic\": \"Not Target\",\n \"Medicolegal Death Investigation\": \"Not Target\",\n};\n\n// ── Tier 3 → Parent Tier 2 lookup ──────────────────────────────────────\nexport const TIER3_TO_TIER2: Record = {\n \"Therapeutic Biotech (Preclinical–Phase II)\": \"Therapeutic Development\",\n \"Pharma R&D & QC\": \"Therapeutic Development\",\n \"Preclinical / Discovery CROs\": \"Contract Research & Manufacturing\",\n \"Bioanalytical / GLP CROs (DMPK, PK/PD)\": \"Contract Research & Manufacturing\",\n \"CDMOs\": \"Contract Research & Manufacturing\",\n \"Platform/Tools Biotech\": \"Life Science Tools & Platforms\",\n \"Molecular and Genetic Specialty\": \"Precision Medicine & Diagnostics\",\n \"Infectious Disease\": \"Precision Medicine & Diagnostics\",\n \"Cancer Diagnostic\": \"Precision Medicine & Diagnostics\",\n \"Meat, Poultry & Seafood Processing\": \"Food & Beverage Manufacturing\",\n \"Dairy Processing\": \"Food & Beverage Manufacturing\",\n \"Beverage Production (Breweries, Wineries, Distilleries)\": \"Food & Beverage Manufacturing\",\n \"Bakery, Snacks & Confectionery\": \"Food & Beverage Manufacturing\",\n \"Fruit & Vegetable Processing\": \"Food & Beverage Manufacturing\",\n \"Ingredients, Flavors & Additives\": \"Food & Beverage Manufacturing\",\n \"Pet Food & Animal Food Manufacturing\": \"Food & Beverage Manufacturing\",\n \"Tobacco Manufacturing\": \"Food & Beverage Manufacturing\",\n \"Contract Food Testing\": \"Contract Food & Beverage Testing\",\n \"Nutraceuticals\": \"Health Supplements\",\n \"Health Supplements\": \"Health Supplements\",\n \"Vitamins\": \"Health Supplements\",\n \"Seed & Trait R&D\": \"Agriculture\",\n \"Soil Testing Services\": \"Agriculture\",\n \"Plant Pathology & Diagnostics\": \"Agriculture\",\n \"Public Agricultural Research\": \"Agriculture\",\n \"Ag Biotech Startups (Biofertilizers, Biocontrol)\": \"Agriculture\",\n \"Specialty Chemicals\": \"Chemicals & Materials\",\n \"Basic & Commodity Chemicals\": \"Chemicals & Materials\",\n \"Polymers, Resins & Plastics\": \"Chemicals & Materials\",\n \"Coatings, Paints & Adhesives\": \"Chemicals & Materials\",\n \"Fertilizers & Agrochemical Manufacturing\": \"Chemicals & Materials\",\n \"Metals & Metallurgy (Primary + Fabricated)\": \"Metals, Minerals & Construction\",\n \"Mining & Mineral Processing\": \"Metals, Minerals & Construction\",\n \"Battery & Rare-Earth Minerals Processing\": \"Metals, Minerals & Construction\",\n \"Building Materials (Cement, Glass, Ceramics)\": \"Metals, Minerals & Construction\",\n \"Engineered Wood & Lumber\": \"Metals, Minerals & Construction\",\n \"Construction & Geotechnical Testing\": \"Metals, Minerals & Construction\",\n \"Automotive & EV (OEMs + Suppliers)\": \"Engineered Products\",\n \"Aerospace & Defense Manufacturing\": \"Engineered Products\",\n \"Medical Devices & Diagnostics Manufacturing\": \"Engineered Products\",\n \"Industrial Machinery & Instrumentation\": \"Engineered Products\",\n \"Plastics & Rubber Products\": \"Engineered Products\",\n \"Appliances & Home Equipment\": \"Engineered Products\",\n \"Mills & Converters\": \"Packaging & Paper\",\n \"Contract Physical & Engineering R&D\": \"Contract Engineering & Analytical\",\n \"Household Cleaning & Chemical Products\": \"Consumer Goods\",\n \"Contract Manufacturers (CPG)\": \"Consumer Goods\",\n \"Apparel, Footwear & Textiles\": \"Consumer Goods\",\n \"Sports & Recreation Equipment\": \"Consumer Goods\",\n \"Furniture\": \"Consumer Goods\",\n \"Cosmetics & Personal Care\": \"Personal Care Products\",\n \"Fragrance & Flavor Houses\": \"Personal Care Products\",\n \"Refinery QC\": \"Oil, Gas & Petrochemical\",\n \"Upstream Core Analysis & Reservoir Fluids\": \"Oil, Gas & Petrochemical\",\n \"Petrochemical Process\": \"Oil, Gas & Petrochemical\",\n \"Fuel & Lubricant Analysis Services\": \"Oil, Gas & Petrochemical\",\n \"Power Plants\": \"Power & Utilities\",\n \"Water & Wastewater Utility\": \"Power & Utilities\",\n \"Energy Storage & Battery R&D\": \"Clean Energy & Storage\",\n \"Renewable Energy\": \"Clean Energy & Storage\",\n \"Water & Wastewater Testing\": \"Environmental Testing\",\n \"Soil & Groundwater Testing\": \"Environmental Testing\",\n \"Air & Emissions Testing\": \"Environmental Testing\",\n \"Industrial Hygiene & Occupational Health\": \"Environmental Testing\",\n \"Ecology & Radiochemistry\": \"Environmental Testing\",\n \"EMC / Compliance (NRTL & 3rd-Party)\": \"Product Safety & Compliance\",\n \"Consumer Product Safety & Claims\": \"Product Safety & Compliance\",\n \"Cannabis Compliance Testing\": \"Cannabis & Hemp Testing\",\n \"Hemp / CBD Testing\": \"Cannabis & Hemp Testing\",\n \"Front-End Fabs\": \"Electronics & Semiconductor\",\n \"OSAT / Test & Packaging\": \"Electronics & Semiconductor\",\n \"Device OEM R&D\": \"Electronics & Semiconductor\",\n \"PCB Assembly QA\": \"Electronics & Semiconductor\",\n \"Regional Reference Labs\": \"Independent Clinical\",\n \"Pathology / Anatomic Pathology Groups\": \"Independent Clinical\",\n \"Toxicology & Drug Testing\": \"Independent Clinical\",\n \"Fertility & Reproductive Medicine\": \"Independent Clinical\",\n \"National Reference\": \"Independent Clinical\",\n \"Private Vet Diagnostic\": \"Veterinary Diagnostics\",\n \"Public Vet Diagnostic (AAVLD)\": \"Veterinary Diagnostics\",\n \"Aquaculture Diagnostic\": \"Veterinary Diagnostics\",\n \"Community Hospital\": \"Hospital & Health System\",\n \"Academic Medical Center\": \"Hospital & Health System\",\n \"Physician Office (POL)\": \"Hospital & Health System\",\n \"Outpatient Clinics\": \"Hospital & Health System\",\n \"Retail Clinic / Pharmacy\": \"Hospital & Health System\",\n \"Dialysis & Specialty Clinic\": \"Hospital & Health System\",\n \"R1 Biomedical Research\": \"University Research\",\n \"R1 Engineering & Materials\": \"University Research\",\n \"R2 / Other University Research\": \"University Research\",\n \"University Core Facilities\": \"University Research\",\n \"Federal National Research\": \"Government & National Research\",\n \"Public Crime\": \"Forensic & Public Safety\",\n \"Private Forensic\": \"Forensic & Public Safety\",\n \"Medicolegal Death Investigation\": \"Forensic & Public Safety\",\n};\n\n// ── Segment from employee count (deterministic) ────────────────────────\nexport type Segment = \"SMB\" | \"Scaled SMB\" | \"Mid-Market\" | \"Enterprise\";\n\nexport function getSegmentFromEmployeeCount(count: number | null): Segment | null {\n if (count === null || count === undefined) return null;\n if (count < 50) return \"SMB\";\n if (count < 250) return \"Scaled SMB\";\n if (count <= 2000) return \"Mid-Market\";\n return \"Enterprise\";\n}\n\n// ── Lab Operation Types ────────────────────────────────────────────────\nexport const LAB_OPERATION_TYPES = [\n \"Process / Continuous\",\n \"Discrete / Lot-Based\",\n \"Research / Non-Production\",\n] as const;\nexport type LabOperationType = typeof LAB_OPERATION_TYPES[number];\n\n// ── Regulatory Frameworks (multi-select) ───────────────────────────────\nexport const REGULATORY_FRAMEWORKS = [\n \"GxP (FDA/EMA)\",\n \"FDA FSMA / USDA\",\n \"NELAP / ISO 17025\",\n \"CLIA / CAP\",\n \"ASTM / ISO 9001\",\n \"EPA Compliance\",\n \"USDA / APHIS\",\n] as const;\nexport type RegulatoryFramework = typeof REGULATORY_FRAMEWORKS[number];\n\n// ── Tier 1 values (for validation) ─────────────────────────────────────\nexport const TIER1_VALUES = [\n \"Life Sciences\",\n \"Food & Beverage\",\n \"Agriculture\",\n \"Manufacturing\",\n \"Energy & Natural Resources\",\n \"Environmental & Compliance Testing\",\n \"Cannabis & Hemp Testing\",\n \"Electronics & Semiconductor\",\n \"Healthcare\",\n \"Academic & Government Research\",\n \"Forensic & Public Safety\",\n] as const;\n\n// ── All valid Tier 2 values ────────────────────────────────────────────\nexport const TIER2_VALUES = Object.keys(TIER2_TO_TIER1);\n\n// ── All valid Tier 3 values ────────────────────────────────────────────\nexport const TIER3_VALUES = Object.keys(TIER3_TO_ICP);\n\n// ── Derive all fields from Tier 3 (the single source of truth) ─────────\nexport function deriveFromTier3(tier3: string): {\n tier2: string;\n tier1: string;\n icpFitTier: ICPFitTier;\n} | null {\n const tier2 = TIER3_TO_TIER2[tier3];\n if (!tier2) return null;\n const tier1 = TIER2_TO_TIER1[tier2];\n if (!tier1) return null;\n const icpFitTier = TIER3_TO_ICP[tier3];\n if (!icpFitTier) return null;\n return { tier2, tier1, icpFitTier };\n}\n\n// ── Contract Model per Tier 3 ──────────────────────────────────────────\nexport type ContractModel = \"In-House\" | \"Contract\" | \"Mixed\";\n\nexport const TIER3_CONTRACT_MODEL: Record = {\n \"Therapeutic Biotech (Preclinical–Phase II)\": \"In-House\",\n \"Pharma R&D & QC\": \"In-House\",\n \"Preclinical / Discovery CROs\": \"Contract\",\n \"Bioanalytical / GLP CROs (DMPK, PK/PD)\": \"Contract\",\n \"CDMOs\": \"Contract\",\n \"Platform/Tools Biotech\": \"In-House\",\n \"Molecular and Genetic Specialty\": \"Mixed\",\n \"Infectious Disease\": \"Mixed\",\n \"Cancer Diagnostic\": \"Mixed\",\n \"Meat, Poultry & Seafood Processing\": \"In-House\",\n \"Dairy Processing\": \"In-House\",\n \"Beverage Production (Breweries, Wineries, Distilleries)\": \"In-House\",\n \"Bakery, Snacks & Confectionery\": \"In-House\",\n \"Fruit & Vegetable Processing\": \"In-House\",\n \"Ingredients, Flavors & Additives\": \"In-House\",\n \"Pet Food & Animal Food Manufacturing\": \"In-House\",\n \"Tobacco Manufacturing\": \"In-House\",\n \"Contract Food Testing\": \"Contract\",\n \"Nutraceuticals\": \"Mixed\",\n \"Health Supplements\": \"Mixed\",\n \"Vitamins\": \"Mixed\",\n \"Seed & Trait R&D\": \"In-House\",\n \"Soil Testing Services\": \"Contract\",\n \"Plant Pathology & Diagnostics\": \"Mixed\",\n \"Public Agricultural Research\": \"In-House\",\n \"Ag Biotech Startups (Biofertilizers, Biocontrol)\": \"In-House\",\n \"Specialty Chemicals\": \"In-House\",\n \"Basic & Commodity Chemicals\": \"In-House\",\n \"Polymers, Resins & Plastics\": \"In-House\",\n \"Coatings, Paints & Adhesives\": \"In-House\",\n \"Fertilizers & Agrochemical Manufacturing\": \"In-House\",\n \"Metals & Metallurgy (Primary + Fabricated)\": \"Mixed\",\n \"Mining & Mineral Processing\": \"Mixed\",\n \"Battery & Rare-Earth Minerals Processing\": \"Mixed\",\n \"Building Materials (Cement, Glass, Ceramics)\": \"In-House\",\n \"Engineered Wood & Lumber\": \"In-House\",\n \"Construction & Geotechnical Testing\": \"Contract\",\n \"Automotive & EV (OEMs + Suppliers)\": \"In-House\",\n \"Aerospace & Defense Manufacturing\": \"In-House\",\n \"Medical Devices & Diagnostics Manufacturing\": \"In-House\",\n \"Industrial Machinery & Instrumentation\": \"In-House\",\n \"Plastics & Rubber Products\": \"In-House\",\n \"Appliances & Home Equipment\": \"In-House\",\n \"Mills & Converters\": \"In-House\",\n \"Contract Physical & Engineering R&D\": \"Contract\",\n \"Household Cleaning & Chemical Products\": \"In-House\",\n \"Contract Manufacturers (CPG)\": \"Contract\",\n \"Apparel, Footwear & Textiles\": \"Mixed\",\n \"Sports & Recreation Equipment\": \"Mixed\",\n \"Furniture\": \"In-House\",\n \"Cosmetics & Personal Care\": \"In-House\",\n \"Fragrance & Flavor Houses\": \"In-House\",\n \"Refinery QC\": \"In-House\",\n \"Upstream Core Analysis & Reservoir Fluids\": \"In-House\",\n \"Petrochemical Process\": \"In-House\",\n \"Fuel & Lubricant Analysis Services\": \"Contract\",\n \"Power Plants\": \"In-House\",\n \"Water & Wastewater Utility\": \"In-House\",\n \"Energy Storage & Battery R&D\": \"In-House\",\n \"Renewable Energy\": \"In-House\",\n \"Water & Wastewater Testing\": \"Contract\",\n \"Soil & Groundwater Testing\": \"Contract\",\n \"Air & Emissions Testing\": \"Contract\",\n \"Industrial Hygiene & Occupational Health\": \"Contract\",\n \"Ecology & Radiochemistry\": \"Contract\",\n \"EMC / Compliance (NRTL & 3rd-Party)\": \"Contract\",\n \"Consumer Product Safety & Claims\": \"Contract\",\n \"Cannabis Compliance Testing\": \"Contract\",\n \"Hemp / CBD Testing\": \"Contract\",\n \"Front-End Fabs\": \"In-House\",\n \"OSAT / Test & Packaging\": \"In-House\",\n \"Device OEM R&D\": \"In-House\",\n \"PCB Assembly QA\": \"In-House\",\n \"Regional Reference Labs\": \"Contract\",\n \"Pathology / Anatomic Pathology Groups\": \"Contract\",\n \"Toxicology & Drug Testing\": \"Contract\",\n \"Fertility & Reproductive Medicine\": \"Contract\",\n \"National Reference\": \"Contract\",\n \"Private Vet Diagnostic\": \"Contract\",\n \"Public Vet Diagnostic (AAVLD)\": \"Contract\",\n \"Aquaculture Diagnostic\": \"Contract\",\n \"Community Hospital\": \"In-House\",\n \"Academic Medical Center\": \"In-House\",\n \"Physician Office (POL)\": \"In-House\",\n \"Outpatient Clinics\": \"In-House\",\n \"Retail Clinic / Pharmacy\": \"In-House\",\n \"Dialysis & Specialty Clinic\": \"In-House\",\n \"R1 Biomedical Research\": \"In-House\",\n \"R1 Engineering & Materials\": \"In-House\",\n \"R2 / Other University Research\": \"In-House\",\n \"University Core Facilities\": \"Contract\",\n \"Federal National Research\": \"In-House\",\n \"Public Crime\": \"In-House\",\n \"Private Forensic\": \"Contract\",\n \"Medicolegal Death Investigation\": \"In-House\",\n};\n",[],[91,112],"1a823c7e-5a2e-11f1-bf62-ee650bb23af1","pipeline.ts","1a823d28-5a2e-11f1-bf62-ee650bb23af1",12,["D",1779928948486],"/**\n * Enrichment Pipeline — orchestrates the full flow:\n * 1. Fetch companies from HubSpot (paginated)\n * 2. Web-enrich each company\n * 3. Classify with AI\n * 4. Store results in SQLite\n *\n * Handles rate limiting, retries, and progress tracking.\n */\nimport { type CompanyProfile, classifyCompany } from \"./classifier.ts\";\nimport { enrichCompany } from \"./web-search.ts\";\nimport {\n initDB,\n createRun,\n updateRunProgress,\n completeRun,\n upsertClassification,\n} from \"./db.ts\";\n\nconst TOKEN = Deno.env.get(\"TOKEN\") || \"\";\nconst HEADERS = {\n Authorization: `Bearer ${TOKEN}`,\n \"Content-Type\": \"application/json\",\n};\n\n// ── HubSpot paginated company fetch ────────────────────────────────────\n\ninterface HubSpotCompany {\n id: string;\n properties: Record;\n}\n\nasync function fetchAllCompanies(\n limit: number = 100,\n maxPages: number = 100,\n): Promise {\n const allCompanies: HubSpotCompany[] = [];\n let after: string | undefined;\n const properties = [\n \"name\", \"domain\", \"industry\", \"numberofemployees\",\n \"city\", \"state\", \"country\", \"description\", \"createdate\",\n ].join(\",\");\n\n for (let page = 0; page < maxPages; page++) {\n const url = new URL(\"https://api.hubapi.com/crm/v3/objects/companies\");\n url.searchParams.set(\"limit\", String(limit));\n url.searchParams.set(\"properties\", properties);\n if (after) url.searchParams.set(\"after\", after);\n\n const res = await fetch(url.toString(), { headers: HEADERS });\n if (!res.ok) {\n const err = await res.text();\n throw new Error(`HubSpot API error (${res.status}): ${err}`);\n }\n\n const data = await res.json();\n allCompanies.push(...(data.results || []));\n\n if (data.paging?.next?.after) {\n after = data.paging.next.after;\n } else {\n break; // No more pages\n }\n\n // Respect rate limits — brief pause between pages\n await sleep(100);\n }\n\n return allCompanies;\n}\n\n// ── Process a single company ───────────────────────────────────────────\n\nasync function processCompany(\n company: HubSpotCompany,\n runId: number,\n): Promise<{ success: boolean; error?: string }> {\n const p = company.properties;\n const name = p.name || \"Unknown\";\n const domain = p.domain || null;\n\n try {\n // Step 1: Web enrichment\n const enrichment = await enrichCompany(name, domain);\n\n // Step 2: Build profile\n const profile: CompanyProfile = {\n hubspotId: company.id,\n name,\n domain,\n industry: p.industry || null,\n employeeCount: p.numberofemployees ? parseInt(p.numberofemployees) : null,\n city: p.city || null,\n state: p.state || null,\n country: p.country || null,\n description: p.description || null,\n webSearchContext: enrichment.context,\n };\n\n // Step 3: AI classification\n const result = await classifyCompany(profile);\n\n // Step 4: Store result\n await upsertClassification({\n runId,\n hubspotId: company.id,\n companyName: name,\n domain,\n employeeCount: profile.employeeCount,\n existingIndustry: p.industry || null,\n tier1: result.tier1,\n tier2: result.tier2,\n tier3: result.tier3,\n icpFitTier: result.icpFitTier,\n segment: result.segment,\n labOperationType: result.labOperationType,\n regulatoryFrameworks: result.regulatoryFrameworks,\n confidence: result.confidence,\n reasoning: result.reasoning,\n webEnrichmentContext: enrichment.context,\n });\n\n return { success: true };\n } catch (error: any) {\n console.error(`Error processing ${name} (${company.id}):`, error.message);\n return { success: false, error: error.message };\n }\n}\n\n// ── Main pipeline runner ───────────────────────────────────────────────\n\nexport interface PipelineOptions {\n batchSize?: number; // companies to process per batch before pausing\n delayBetweenMs?: number; // ms delay between companies (rate limiting)\n maxCompanies?: number; // cap for testing (0 = all)\n dryRun?: boolean; // if true, fetch but don't classify\n}\n\nexport interface PipelineProgress {\n runId: number;\n total: number;\n processed: number;\n succeeded: number;\n failed: number;\n status: \"running\" | \"completed\" | \"error\";\n errors: Array<{ company: string; error: string }>;\n}\n\nexport async function runPipeline(\n options: PipelineOptions = {},\n): Promise {\n const {\n batchSize = 10,\n delayBetweenMs = 2000, // 2s between companies (LLM + web search cost)\n maxCompanies = 0,\n dryRun = false,\n } = options;\n\n // Initialize database\n await initDB();\n\n // Fetch all companies from HubSpot\n console.log(\"Fetching companies from HubSpot...\");\n let companies = await fetchAllCompanies();\n console.log(`Fetched ${companies.length} companies`);\n\n if (maxCompanies > 0) {\n companies = companies.slice(0, maxCompanies);\n console.log(`Limited to ${companies.length} for this run`);\n }\n\n const runId = await createRun(companies.length);\n\n const progress: PipelineProgress = {\n runId,\n total: companies.length,\n processed: 0,\n succeeded: 0,\n failed: 0,\n status: \"running\",\n errors: [],\n };\n\n if (dryRun) {\n console.log(\"DRY RUN — fetched companies but skipping classification\");\n progress.status = \"completed\";\n return progress;\n }\n\n // Process in batches\n for (let i = 0; i < companies.length; i++) {\n const company = companies[i];\n const result = await processCompany(company, runId);\n\n progress.processed++;\n if (result.success) {\n progress.succeeded++;\n } else {\n progress.failed++;\n progress.errors.push({\n company: company.properties.name || company.id,\n error: result.error || \"Unknown error\",\n });\n }\n\n // Update run progress every 10 companies\n if (progress.processed % 10 === 0 || progress.processed === companies.length) {\n await updateRunProgress(runId, progress.processed);\n console.log(\n `Progress: ${progress.processed}/${progress.total} ` +\n `(${progress.succeeded} ok, ${progress.failed} failed)`,\n );\n }\n\n // Rate limit delay\n if (i < companies.length - 1) {\n await sleep(delayBetweenMs);\n }\n }\n\n await completeRun(runId);\n progress.status = \"completed\";\n\n console.log(\n `Pipeline complete: ${progress.succeeded}/${progress.total} succeeded, ` +\n `${progress.failed} failed`,\n );\n\n return progress;\n}\n\nfunction sleep(ms: number): Promise {\n return new Promise((resolve) => setTimeout(resolve, ms));\n}\n",[],[91,120],"081e5194-5a2e-11f1-9d85-ee650bb23af1","db.ts","081e528e-5a2e-11f1-9d85-ee650bb23af1",11,["D",1779928917630],"/**\n * SQLite schema and queries for the enrichment pipeline.\n * Stores classification results, review status, and audit log.\n */\nimport { sqlite } from \"https://esm.town/v/std/sqlite/main.ts\";\n\nexport async function initDB() {\n await sqlite.batch([\n {\n sql: `CREATE TABLE IF NOT EXISTS enrichment_runs (\n id INTEGER PRIMARY KEY AUTOINCREMENT,\n started_at TEXT NOT NULL DEFAULT (datetime('now')),\n completed_at TEXT,\n total_companies INTEGER DEFAULT 0,\n processed INTEGER DEFAULT 0,\n status TEXT NOT NULL DEFAULT 'running'\n )`,\n },\n {\n sql: `CREATE TABLE IF NOT EXISTS company_classifications (\n id INTEGER PRIMARY KEY AUTOINCREMENT,\n run_id INTEGER,\n hubspot_id TEXT NOT NULL,\n company_name TEXT NOT NULL,\n domain TEXT,\n employee_count INTEGER,\n -- Existing HubSpot values\n existing_industry TEXT,\n -- AI Classification results\n tier1 TEXT,\n tier2 TEXT,\n tier3 TEXT,\n icp_fit_tier TEXT,\n segment TEXT,\n lab_operation_type TEXT,\n regulatory_frameworks TEXT,\n confidence INTEGER,\n reasoning TEXT,\n web_enrichment_context TEXT,\n -- Review status\n review_status TEXT NOT NULL DEFAULT 'pending',\n reviewed_by TEXT,\n reviewed_at TEXT,\n review_notes TEXT,\n -- Push status\n pushed_to_hubspot INTEGER DEFAULT 0,\n pushed_at TEXT,\n -- Timestamps\n created_at TEXT NOT NULL DEFAULT (datetime('now')),\n updated_at TEXT NOT NULL DEFAULT (datetime('now')),\n UNIQUE(hubspot_id)\n )`,\n },\n {\n sql: `CREATE TABLE IF NOT EXISTS audit_log (\n id INTEGER PRIMARY KEY AUTOINCREMENT,\n hubspot_id TEXT NOT NULL,\n action TEXT NOT NULL,\n old_values TEXT,\n new_values TEXT,\n performed_by TEXT DEFAULT 'system',\n created_at TEXT NOT NULL DEFAULT (datetime('now'))\n )`,\n },\n ]);\n}\n\nexport interface StoredClassification {\n id: number;\n run_id: number;\n hubspot_id: string;\n company_name: string;\n domain: string | null;\n employee_count: number | null;\n existing_industry: string | null;\n tier1: string;\n tier2: string;\n tier3: string;\n icp_fit_tier: string;\n segment: string | null;\n lab_operation_type: string | null;\n regulatory_frameworks: string | null;\n confidence: number;\n reasoning: string;\n web_enrichment_context: string | null;\n review_status: string;\n reviewed_by: string | null;\n reviewed_at: string | null;\n review_notes: string | null;\n pushed_to_hubspot: number;\n pushed_at: string | null;\n created_at: string;\n updated_at: string;\n}\n\nexport async function upsertClassification(data: {\n runId: number;\n hubspotId: string;\n companyName: string;\n domain: string | null;\n employeeCount: number | null;\n existingIndustry: string | null;\n tier1: string;\n tier2: string;\n tier3: string;\n icpFitTier: string;\n segment: string | null;\n labOperationType: string | null;\n regulatoryFrameworks: string[];\n confidence: number;\n reasoning: string;\n webEnrichmentContext: string | null;\n}) {\n await sqlite.execute({\n sql: `INSERT INTO company_classifications (\n run_id, hubspot_id, company_name, domain, employee_count,\n existing_industry, tier1, tier2, tier3, icp_fit_tier,\n segment, lab_operation_type, regulatory_frameworks,\n confidence, reasoning, web_enrichment_context,\n review_status, updated_at\n ) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, 'pending', datetime('now'))\n ON CONFLICT(hubspot_id) DO UPDATE SET\n run_id = excluded.run_id,\n company_name = excluded.company_name,\n domain = excluded.domain,\n employee_count = excluded.employee_count,\n existing_industry = excluded.existing_industry,\n tier1 = excluded.tier1,\n tier2 = excluded.tier2,\n tier3 = excluded.tier3,\n icp_fit_tier = excluded.icp_fit_tier,\n segment = excluded.segment,\n lab_operation_type = excluded.lab_operation_type,\n regulatory_frameworks = excluded.regulatory_frameworks,\n confidence = excluded.confidence,\n reasoning = excluded.reasoning,\n web_enrichment_context = excluded.web_enrichment_context,\n review_status = CASE WHEN company_classifications.pushed_to_hubspot = 1 THEN company_classifications.review_status ELSE 'pending' END,\n updated_at = datetime('now')`,\n args: [\n data.runId,\n data.hubspotId,\n data.companyName,\n data.domain,\n data.employeeCount,\n data.existingIndustry,\n data.tier1,\n data.tier2,\n data.tier3,\n data.icpFitTier,\n data.segment,\n data.labOperationType,\n JSON.stringify(data.regulatoryFrameworks),\n data.confidence,\n data.reasoning,\n data.webEnrichmentContext,\n ],\n });\n}\n\nexport async function getClassifications(filters: {\n status?: string;\n icpFitTier?: string;\n minConfidence?: number;\n limit?: number;\n offset?: number;\n}): Promise<{ rows: StoredClassification[]; total: number }> {\n const where: string[] = [];\n const args: any[] = [];\n\n if (filters.status) {\n where.push(\"review_status = ?\");\n args.push(filters.status);\n }\n if (filters.icpFitTier) {\n where.push(\"icp_fit_tier = ?\");\n args.push(filters.icpFitTier);\n }\n if (filters.minConfidence !== undefined) {\n where.push(\"confidence >= ?\");\n args.push(filters.minConfidence);\n }\n\n const whereClause = where.length > 0 ? `WHERE ${where.join(\" AND \")}` : \"\";\n const limit = filters.limit || 50;\n const offset = filters.offset || 0;\n\n const countResult = await sqlite.execute({\n sql: `SELECT COUNT(*) as count FROM company_classifications ${whereClause}`,\n args,\n });\n const total = (countResult.rows[0] as any)?.count || 0;\n\n const result = await sqlite.execute({\n sql: `SELECT * FROM company_classifications ${whereClause}\n ORDER BY confidence DESC, company_name ASC\n LIMIT ? OFFSET ?`,\n args: [...args, limit, offset],\n });\n\n return { rows: result.rows as StoredClassification[], total };\n}\n\nexport async function updateReviewStatus(\n hubspotId: string,\n status: \"approved\" | \"rejected\",\n notes?: string,\n) {\n await sqlite.execute({\n sql: `UPDATE company_classifications\n SET review_status = ?, reviewed_at = datetime('now'), review_notes = ?, updated_at = datetime('now')\n WHERE hubspot_id = ?`,\n args: [status, notes || null, hubspotId],\n });\n}\n\nexport async function bulkUpdateReviewStatus(\n hubspotIds: string[],\n status: \"approved\" | \"rejected\",\n) {\n const placeholders = hubspotIds.map(() => \"?\").join(\",\");\n await sqlite.execute({\n sql: `UPDATE company_classifications\n SET review_status = ?, reviewed_at = datetime('now'), updated_at = datetime('now')\n WHERE hubspot_id IN (${placeholders})`,\n args: [status, ...hubspotIds],\n });\n}\n\nexport async function createRun(totalCompanies: number): Promise {\n const result = await sqlite.execute({\n sql: `INSERT INTO enrichment_runs (total_companies) VALUES (?)`,\n args: [totalCompanies],\n });\n return Number(result.lastInsertRowid);\n}\n\nexport async function updateRunProgress(runId: number, processed: number) {\n await sqlite.execute({\n sql: `UPDATE enrichment_runs SET processed = ? WHERE id = ?`,\n args: [processed, runId],\n });\n}\n\nexport async function completeRun(runId: number) {\n await sqlite.execute({\n sql: `UPDATE enrichment_runs SET status = 'completed', completed_at = datetime('now') WHERE id = ?`,\n args: [runId],\n });\n}\n\nexport async function getLatestRun() {\n const result = await sqlite.execute(\n `SELECT * FROM enrichment_runs ORDER BY id DESC LIMIT 1`,\n );\n return result.rows[0] || null;\n}\n\nexport async function getStats() {\n const result = await sqlite.execute(`\n SELECT\n COUNT(*) as total,\n SUM(CASE WHEN review_status = 'pending' THEN 1 ELSE 0 END) as pending,\n SUM(CASE WHEN review_status = 'approved' THEN 1 ELSE 0 END) as approved,\n SUM(CASE WHEN review_status = 'rejected' THEN 1 ELSE 0 END) as rejected,\n SUM(CASE WHEN pushed_to_hubspot = 1 THEN 1 ELSE 0 END) as pushed,\n AVG(confidence) as avg_confidence,\n SUM(CASE WHEN icp_fit_tier = 'Bullseye' THEN 1 ELSE 0 END) as bullseye,\n SUM(CASE WHEN icp_fit_tier = 'Ring 1' THEN 1 ELSE 0 END) as ring1,\n SUM(CASE WHEN icp_fit_tier = 'Ring 2' THEN 1 ELSE 0 END) as ring2,\n SUM(CASE WHEN icp_fit_tier = 'Not Target' THEN 1 ELSE 0 END) as not_target\n FROM company_classifications\n `);\n return result.rows[0] || {};\n}\n",[],[91,128],"e1f0c2b8-5a2d-11f1-83ca-ee650bb23af1","classifier.ts","e1f0c376-5a2d-11f1-83ca-ee650bb23af1",9,["D",1779928853581],"/**\n * AI Classifier — Uses Claude to classify companies into the QBench taxonomy.\n * The LLM picks Tier 2 (mid-tier) and Tier 3 (niche).\n * Everything else is derived deterministically from taxonomy lookups.\n */\nimport Anthropic from \"npm:@anthropic-ai/sdk@0.39.0\";\nimport {\n TIER2_VALUES,\n TIER3_VALUES,\n TIER3_TO_TIER2,\n LAB_OPERATION_TYPES,\n REGULATORY_FRAMEWORKS,\n deriveFromTier3,\n getSegmentFromEmployeeCount,\n type ICPFitTier,\n type LabOperationType,\n type RegulatoryFramework,\n type Segment,\n} from \"./taxonomy.ts\";\n\nconst client = new Anthropic();\n\nexport interface CompanyProfile {\n hubspotId: string;\n name: string;\n domain: string | null;\n industry: string | null; // existing HubSpot industry value\n employeeCount: number | null;\n city: string | null;\n state: string | null;\n country: string | null;\n description: string | null; // from HubSpot\n webSearchContext: string | null; // from web enrichment\n}\n\nexport interface ClassificationResult {\n tier3: string;\n tier2: string;\n tier1: string;\n icpFitTier: ICPFitTier;\n segment: Segment | null;\n labOperationType: LabOperationType | null;\n regulatoryFrameworks: RegulatoryFramework[];\n confidence: number; // 0-100\n reasoning: string;\n}\n\nconst SYSTEM_PROMPT = `You are an expert B2B industry classifier for QBench, a Laboratory Information Management System (LIMS) company. Your job is to classify companies into QBench's proprietary industry taxonomy based on all available evidence.\n\n## YOUR TASK\nGiven a company profile (name, domain, location, employee count, existing HubSpot industry, web search context), classify it into:\n1. **Tier 3 (Niche)** — the most specific classification. This is the PRIMARY output.\n2. **Lab Operation Type** — Process/Continuous, Discrete/Lot-Based, or Research/Non-Production\n3. **Regulatory Frameworks** — which regulatory regimes apply (can be multiple or none)\n4. **Confidence** — 0-100 score reflecting classification certainty\n5. **Reasoning** — 2-3 sentences explaining your classification logic\n\n## VALID TIER 3 VALUES (you MUST pick exactly one):\n${TIER3_VALUES.map(v => `- ${v}`).join(\"\\n\")}\n\n## VALID LAB OPERATION TYPES (pick exactly one, or null if unclear):\n${Array.from(LAB_OPERATION_TYPES).map(v => `- ${v}`).join(\"\\n\")}\n\n## VALID REGULATORY FRAMEWORKS (pick zero or more):\n${Array.from(REGULATORY_FRAMEWORKS).map(v => `- ${v}`).join(\"\\n\")}\n\n## CLASSIFICATION RULES\n- Focus on what the company DOES and what KIND OF LAB they operate (or would operate)\n- A \"lab\" in QBench's context = any facility doing testing, QC, R&D, or analytical work\n- If a company has no lab or testing component at all, classify into the CLOSEST industry niche anyway — the ICP system will handle disqualification\n- Prefer SPECIFIC niches over general ones\n- If a company could fit multiple niches, pick the PRIMARY business activity\n- Use employee count for segment sizing but NOT for niche selection\n- Web search context is your most valuable signal — use it heavily\n\n## CONFIDENCE SCORING\n- 90-100: Clear match — company description, domain, and industry all align to one niche\n- 70-89: Strong match — most signals align, minor ambiguity\n- 50-69: Moderate — some signals conflict or limited info available\n- 30-49: Low — mostly guessing from company name/domain alone\n- 0-29: Very low — almost no useful information\n\n## RESPONSE FORMAT\nRespond with ONLY a JSON object, no markdown:\n{\n \"tier3\": \"exact Tier 3 value from the list above\",\n \"labOperationType\": \"Process / Continuous\" | \"Discrete / Lot-Based\" | \"Research / Non-Production\" | null,\n \"regulatoryFrameworks\": [\"framework1\", \"framework2\"],\n \"confidence\": 75,\n \"reasoning\": \"Brief explanation of why this classification was chosen.\"\n}`;\n\nexport async function classifyCompany(profile: CompanyProfile): Promise {\n const userMessage = buildUserMessage(profile);\n\n const response = await client.messages.create({\n model: \"claude-sonnet-4-20250514\",\n max_tokens: 500,\n temperature: 0.1, // low temp for consistency\n system: SYSTEM_PROMPT,\n messages: [{ role: \"user\", content: userMessage }],\n });\n\n const text = response.content[0].type === \"text\" ? response.content[0].text : \"\";\n const parsed = parseClassificationResponse(text, profile.employeeCount);\n\n return parsed;\n}\n\nfunction buildUserMessage(profile: CompanyProfile): string {\n const parts = [`## Company Profile`];\n parts.push(`**Name:** ${profile.name}`);\n if (profile.domain) parts.push(`**Domain:** ${profile.domain}`);\n if (profile.industry) parts.push(`**Existing HubSpot Industry:** ${profile.industry}`);\n if (profile.employeeCount) parts.push(`**Employee Count:** ${profile.employeeCount}`);\n const location = [profile.city, profile.state, profile.country].filter(Boolean).join(\", \");\n if (location) parts.push(`**Location:** ${location}`);\n if (profile.description) parts.push(`**Description:** ${profile.description}`);\n if (profile.webSearchContext) {\n parts.push(`\\n## Web Search Context`);\n parts.push(profile.webSearchContext);\n }\n return parts.join(\"\\n\");\n}\n\nfunction parseClassificationResponse(text: string, employeeCount: number | null): ClassificationResult {\n // Strip markdown code fences if present\n const cleaned = text.replace(/```json\\n?/g, \"\").replace(/```\\n?/g, \"\").trim();\n const parsed = JSON.parse(cleaned);\n\n const tier3 = parsed.tier3;\n if (!TIER3_VALUES.includes(tier3)) {\n throw new Error(`Invalid Tier 3 value from LLM: \"${tier3}\"`);\n }\n\n // Derive Tier 2, Tier 1, and ICP deterministically\n const derived = deriveFromTier3(tier3);\n if 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