A full-featured Telegram bot that accepts text descriptions, photos, or PDF floor plans and returns detailed cost estimates with work breakdown. Powered by GPT-4 Vision / Gemini 2.0, vector search, and the open-source DDC CWICR database (55,000+ construction rates). Who's it for - Contractors & Estimators who need estimates from any input format - Construction managers evaluating scope from site photos or drawings - Architects getting quick cost feedback on floor plans - Real estate professional

A full-featured Telegram bot that accepts text descriptions, photos, or PDF floor plans and returns detailed cost estimates with work breakdown. Powered by GPT-4 Vision / Gemini 2.0, vector search, and the open-source DDC CWICR database (55,000+ construction rates). Who's it for - Contractors & Estimators who need estimates from any input format - Construction managers evaluating scope from site photos or drawings - Architects getting quick cost feedback on floor plans - Real estate professionals assessing renovation costs - Project managers doing rapid feasibility checks via mobile What it does 1. Receives text / photo / PDF via Telegram 2. Analyzes input with AI (Gemini 2.0 Flash or GPT-4 Vision) 3. Extracts work items with quantities and units 4. Searches DDC CWICR vector database for matching rates 5. Generates professional HTML report with full cost breakdown 6. Exports results as Excel or PDF Supports 9 languages: 🇩🇪 DE · 🇬🇧 EN · 🇷🇺 RU · 🇪🇸 ES · 🇫🇷 FR · 🇮🇹 IT · 🇵🇱 PL · 🇧🇷 PT · 🇺🇦 UK How it works Input Types | Type | Description | AI Used | |------|-------------|---------| | 📝 Text | Work lists, specifications, notes | OpenAI GPT-4 | | 📷 Photo | Construction site photos (up to 4) | GPT-4 Vision / Gemini | | 📄 PDF | Floor plans, architectural drawings | Gemini 2.0 Flash | Route Actions (17 total) | # | Action | Description | |---|--------|-------------| | 0 | showlang | Language selection menu | | 1 | askphoto | Request photo upload | | 2 | langselected | Save language preference | | 3 | showanalyze | Photo analysis options | | 4 | analyze | Run AI vision analysis | | 5 | showeditmenu | Edit work quantities | | 6 | worksupdated | After quantity change | | 7 | asknewwork | Add manual work item | | 8 | startcalc | Start cost calculation | | 9 | showhelp | Display help message | | 10 | viewdetails | Show resource details | | 11 | exportexcel | Generate CSV export | | 12 | exportpdf | Generate PDF export | | 13 | processpdf | Analyze PDF floor plan | | 14 | analyzetext | Parse text description | | 15 | refine | Re-analyze with context | | 16 | fallback | Handle unknown input | Prerequisites | Component | Requirement | |-----------|-------------| | n8n | v1.30+ with Telegram Trigger | | Telegram Bot | Token from @BotFather | | OpenAI API | For embeddings + text parsing | | Gemini API | For Vision (photos/PDF) — or use GPT-4 Vision | | Qdrant | Vector DB with DDC CWICR collections | | DDC CWICR Data | github.com/datadrivenconstruction/DDC-CWICR | Setup 1. Configure 🔑 TOKEN Node 2. Vision Provider Selection - AIPROVIDER: "gemini" → Gemini 2.0 Flash (recommended for photos + PDF) - AIPROVIDER: "openai" → GPT-4 Vision (photos only) 3. n8n Credentials 1. Settings → Credentials → Add → Telegram API 2. Enter bot token, save 3. Select credential in Telegram Trigger node 4. Qdrant Collections Load DDC CWICR embeddings for target languages (example for Russian): 5. Activate & Test 1. Activate workflow 2. Send /start to your bot 3. Select language → send photo/text/PDF Features | Feature | Description | |---------|-------------| | 📷 Photo Analysis | GPT-4 Vision or Gemini 2.0 for site photos | | 📄 PDF Processing | Floor plan analysis with room extraction | | 📝 Text Parsing | Natural language work lists | | 🔍 Vector Search | Semantic matching via Qdrant + OpenAI embeddings | | 🤖 AI Reranking | LLM-based result scoring for accuracy | | ✏️ Inline Editing | Modify quantities via Telegram buttons | | 📊 HTML Report | Professional expandable report with KPIs | | 📑 Excel Export | CSV with full work breakdown | | 📄 PDF Export | HTML-based PDF document | | 🌍 9 Languages | Full UI + database localization | | 💾 Session State | Multi-turn conversation support | | 🔧 Refine Mode | Re-analyze with additional context | Example Workflow User: /start Bot: Language selection menu (9 options) User: Selects 🇷🇺 Russian Bot: "Отправьте фото, PDF или текстовое описание работ" User: Sends bathroom photo Bot: "📷 Анализ фото... ⏳" Bot: Shows detected works: User: Taps 📊 Calculate Bot: Shows progress per item, then final result: HTML Report Features - KPI Cards: Total cost, item count, labor days, cost breakdown % - Expandable rows: Click work item to show resources - Resource tags: Color-coded (Labor/Material/Machine) - Scope of work: Expandable detailed descriptions - Quality indicators: Match quality dots (high/medium/low) - Responsive design: Works on mobile and desktop - Export buttons: Expand/Collapse all Notes & Tips - Photo tips: Capture full room, include reference objects (doors, tiles) - PDF support: Works best with clear floor plans and room schedules - Text input: Supports lists, tables, free-form descriptions - Rate accuracy: Depends on DDC CWICR coverage for your region - Session timeout: User sessions persist across messages - Extend: Chain with CRM, project management, or notification tools Categories AI · Communication · Data Extraction · Document Ops Tags telegram-bot, construction, cost-estimation, gpt-4-vision, gemini, pdf-analysis, qdrant, vector-search, multilingual, html-report --- Author DataDrivenConstruction.io info@datadrivenconstruction.io Consulting & Training We help construction, engineering, and technology firms implement: - AI-powered estimation systems (text, photo, PDF) - Multi-channel bot integrations (Telegram, WhatsApp, Web) - Vector database solutions for construction data - Multilingual cost database deployment Contact us to test with your data or adapt to your project requirements. Resources - DDC CWICR Database: GitHub - Qdrant Documentation: qdrant.tech/documentation - Gemini API: aistudio.google.com - n8n Telegram Trigger: docs.n8n.io --- ⭐ Star us on GitHub! github.com/datadrivenconstruction/DDC-CWICR
Download the workflow JSON file after purchase.
Open n8n → click the menu → Import from File.
Select the downloaded JSON and import.
Set up credentials for each node that requires them.
Click Execute Workflow to test, then activate.
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