Estimate construction costs from text, photos and PDFs with Telegram, GPT‑4/Gemini and DDC CWICR

Created by

Artem Boiko

Last update

Last update 12 hours ago

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

Receives text / photo / PDF via Telegram
Analyzes input with AI (Gemini 2.0 Flash or GPT-4 Vision)
Extracts work items with quantities and units
Searches DDC CWICR vector database for matching rates
Generates professional HTML report with full cost breakdown
Exports results as Excel or PDF

Supports 9 languages: 🇩🇪 DE · 🇬🇧 EN · 🇷🇺 RU · 🇪🇸 ES · 🇫🇷 FR · 🇮🇹 IT · 🇵🇱 PL · 🇧🇷 PT · 🇺🇦 UK

How it works

┌─────────────────────────────────────────────────────────────────────┐
│                        TELEGRAM INPUT                                │
│  📝 Text Description  │  📷 Construction Photo  │  📄 PDF Floor Plan │
└─────────────────────────────────────────────────────────────────────┘
                                    ↓
┌─────────────────────────────────────────────────────────────────────┐
│                         MAIN ROUTER                                  │
│  Parse message → Detect content type → Route to handler (17 actions) │
└─────────────────────────────────────────────────────────────────────┘
                                    ↓
         ┌──────────────────────────┼──────────────────────────┐
         ↓                          ↓                          ↓
┌─────────────────┐     ┌─────────────────┐     ┌─────────────────┐
│  Text LLM       │     │  Vision API     │     │  Vision PDF     │
│  Parse works    │     │  Analyze photo  │     │  Read floor plan│
│  from text      │     │  GPT-4/Gemini   │     │  Gemini 2.0     │
└─────────────────┘     └─────────────────┘     └─────────────────┘
         └──────────────────────────┼──────────────────────────┘
                                    ↓
┌─────────────────────────────────────────────────────────────────────┐
│                    CALCULATION LOOP                                  │
│  For each work item:                                                 │
│  1️⃣ Transform query → 2️⃣ Optimize search → 3️⃣ Get embedding         │
│  4️⃣ Qdrant search → 5️⃣ Score results → 6️⃣ AI rerank → 7️⃣ Calculate  │
└─────────────────────────────────────────────────────────────────────┘
                                    ↓
┌─────────────────────────────────────────────────────────────────────┐
│                      OUTPUT                                          │
│  📊 Telegram message  │  🌐 HTML Report  │  📑 Excel  │  📄 PDF      │
└─────────────────────────────────────────────────────────────────────┘

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	show_lang	Language selection menu
1	ask_photo	Request photo upload
2	lang_selected	Save language preference
3	show_analyze	Photo analysis options
4	analyze	Run AI vision analysis
5	show_edit_menu	Edit work quantities
6	works_updated	After quantity change
7	ask_new_work	Add manual work item
8	start_calc	Start cost calculation
9	show_help	Display help message
10	view_details	Show resource details
11	export_excel	Generate CSV export
12	export_pdf	Generate PDF export
13	process_pdf	Analyze PDF floor plan
14	analyze_text	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

{
  "bot_token": "YOUR_TELEGRAM_BOT_TOKEN",
  "AI_PROVIDER": "gemini",
  "GEMINI_API_KEY": "YOUR_GEMINI_KEY",
  "OPENAI_API_KEY": "YOUR_OPENAI_KEY",
  "QDRANT_URL": "http://localhost:6333",
  "QDRANT_API_KEY": "YOUR_QDRANT_KEY"
}

2. Vision Provider Selection

AI_PROVIDER: "gemini" → Gemini 2.0 Flash (recommended for photos + PDF)
AI_PROVIDER: "openai" → GPT-4 Vision (photos only)

3. n8n Credentials

Settings → Credentials → Add → Telegram API
Enter bot token, save
Select credential in Telegram Trigger node

4. Qdrant Collections

Load DDC CWICR embeddings for target languages (example for Russian):

RU_STPETERSBURG_workitems_costs_resources_EMBEDDINGS_3072_DDC_CWICR

5. Activate & Test

Activate workflow
Send /start to your bot
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:

🏠 Ванная комната — 4.5 m²

Найдено 12 работ:
1. Демонтаж плитки стен — 18 m²
2. Демонтаж плитки пола — 4.5 m²
3. Гидроизоляция пола — 4.5 m²
4. Гидроизоляция стен — 8 m²
5. Стяжка пола — 4.5 m²
6. Укладка плитки стены — 18 m²
7. Укладка плитки пол — 4.5 m²
8. Установка унитаза — 1 шт
9. Установка раковины — 1 шт
10. Установка смесителя — 2 шт
...

[✏️ Редактировать] [📊 Рассчитать]

User: Taps 📊 Calculate
Bot: Shows progress per item, then final result:

✅ Смета готова — 12 позиций

💰 Итого: ₽ 89,450

Работа: ₽ 35,200 (39%)
Материалы: ₽ 48,750 (55%)
Механизмы: ₽ 5,500 (6%)

[📋 Детали] [↓ Excel] [↓ PDF] [↻ Заново]

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

Author

DataDrivenConstruction.io
https://DataDrivenConstruction.io
[email protected]

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