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Generate photo-based construction cost estimates with GPT-4 Vision and DDC CWICR

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Created by: Artem Boiko || datadrivenconstruction

Artem Boiko

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Last update 2 days ago

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Upload a construction photo via web form → get a detailed cost estimate with work breakdown, resource costs, and professional HTML report. Powered by GPT-4 Vision and the open-source DDC CWICR database (55,000+ work items).

Who's it for

  • Site managers who need quick estimates from mobile photos
  • Renovation contractors evaluating project scope from initial site visit
  • Real estate inspectors estimating repair costs
  • Construction consultants providing rapid ballpark figures
  • DIY enthusiasts planning home improvement budgets

What it does

  1. Collects photo + region/language via n8n Form
  2. Analyzes photo with GPT-4 Vision (room type, elements, dimensions)
  3. Decomposes visible elements into construction work items
  4. Searches DDC CWICR vector database for matching rates
  5. Generates professional HTML report with cost breakdown

Supports 9 regions: 🇩🇪 Berlin · 🇬🇧 Toronto · 🇷🇺 St. Petersburg · 🇪🇸 Barcelona · 🇫🇷 Paris · 🇧🇷 São Paulo · 🇨🇳 Shanghai · 🇦🇪 Dubai · 🇮🇳 Mumbai

How it works

┌──────────────┐    ┌───────────────┐    ┌───────────────┐    ┌──────────────┐
│  Web Form    │ →  │  STAGE 1      │ →  │  STAGE 4      │ →  │  Loop Works  │
│  Photo+Lang  │    │  GPT-4 Vision │    │  Decompose    │    │  per item    │
└──────────────┘    └───────────────┘    └───────────────┘    └──────────────┘
                           ↓                     ↓                    ↓
                    ┌─────────────────────────────────────────────────────┐
                    │  Identify room, elements, fixtures, dimensions      │
                    │  → Break down into 15-40 construction work items    │
                    └─────────────────────────────────────────────────────┘
                                                                     ↓
┌──────────────┐    ┌───────────────┐    ┌───────────────┐    ┌──────────────┐
│  HTML Report │ ←  │  STAGE 7.5    │ ←  │  STAGE 5      │ ←  │  Qdrant      │
│  Response    │    │  Aggregate    │    │  Parse+Score  │    │  Vector DB   │
└──────────────┘    └───────────────┘    └───────────────┘    └──────────────┘

Pipeline stages:

Stage Node Description
1 GPT-4 Vision Analyzes photo: room type, elements, materials, dimensions
4 GPT-4 Decompose Breaks elements into work items with quantities
5 Vector Search + Score Finds matching rates in DDC CWICR, quality scoring
7.5 Aggregate & Validate Sums costs, groups by phase, validates results
9 HTML Report Generates professional estimate document

Prerequisites

Component Requirement
n8n v1.30+ with Form Trigger support
OpenAI API GPT-4 Vision + Embeddings access
Qdrant Vector DB with DDC CWICR collections
DDC CWICR Data github.com/datadrivenconstruction/DDC-CWICR

Setup

1. n8n Credentials (Settings → Credentials)

  • OpenAI API — required (GPT-4 Vision + text-embedding-3-large)
  • Qdrant API — your Qdrant instance connection

2. Qdrant Collections

Load DDC CWICR embeddings for your target regions:

DE_BERLIN_workitems_costs_resources_EMBEDDINGS_3072_DDC_CWICR
ENG_TORONTO_workitems_costs_resources_EMBEDDINGS_3072_DDC_CWICR
RU_STPETERSBURG_workitems_costs_resources_EMBEDDINGS_3072_DDC_CWICR
ES_BARCELONA_workitems_costs_resources_EMBEDDINGS_3072_DDC_CWICR
FR_PARIS_workitems_costs_resources_EMBEDDINGS_3072_DDC_CWICR
PT_SAOPAULO_workitems_costs_resources_EMBEDDINGS_3072_DDC_CWICR
ZH_SHANGHAI_workitems_costs_resources_EMBEDDINGS_3072_DDC_CWICR
AR_DUBAI_workitems_costs_resources_EMBEDDINGS_3072_DDC_CWICR
HI_MUMBAI_workitems_costs_resources_EMBEDDINGS_3072_DDC_CWICR

3. Activate Workflow

  1. Import JSON into n8n
  2. Link OpenAI + Qdrant credentials to respective nodes
  3. Activate workflow
  4. Access form at: https://your-n8n/form/photo-estimate-pro-v3

Features

Feature Description
📸 Photo Analysis GPT-4 Vision identifies room type, elements, fixtures
📏 Dimension Estimation Uses reference objects (doors, tiles) for sizing
🔧 Work Decomposition Breaks down to 15-40 specific work items
🎯 Quality Scoring Rates match quality (high/medium/low/not_found)
📊 Phase Grouping PREPARATION → MAIN → FINISHING → MEP
💰 Cost Breakdown Labor, materials, machines per item
✅ Validation Warns if <50% rates found or missing demolition
🌍 9 Languages Full localization + regional pricing

Form Fields

Field Type Options
📷 Upload Photo File .jpg, .png, .webp
🌍 Region & Language Dropdown 9 regions with currencies
🏗️ Work Type Dropdown New / Renovation / Repair / Auto
📝 Description Textarea Optional context

Example Output

Input: Bathroom photo (renovation)
Region: 🇩🇪 German - Berlin (EUR €)

Generated Work Items:

PREPARATION (3 items)
├── Demolition of wall tiles — 12 m² — €180
├── Demolition of floor tiles — 4.5 m² — €95
└── Disposal of construction waste — 0.8 m³ — €120

MAIN (8 items)
├── Floor waterproofing — 4.5 m² — €225
├── Wall waterproofing wet zone — 8 m² — €280
├── Floor screed — 4.5 m² — €135
├── Wall tiling — 22 m² — €880
├── Floor tiling — 4.5 m² — €225
├── Toilet installation — 1 pcs — €320
├── Sink installation — 1 pcs — €185
└── Shower cabin installation — 1 pcs — €450

FINISHING (3 items)
├── Ceiling painting — 4.5 m² — €68
├── Grouting — 26.5 m² — €133
└── Silicone sealing — 8 m — €48

MEP (4 items)
├── Socket installation — 2 pcs — €90
├── Light point installation — 2 pcs — €120
├── Mixer/faucet installation — 2 pcs — €160
└── Ventilation installation — 1 pcs — €85

─────────────────────────────────────
TOTAL: €3,799.00
Labor: €1,520 · Materials: €1,900 · Machines: €379
Quality: 78% high match · 18 work items

Quality Scoring System

Score Level Meaning
60-100 🟢 High Exact match with resources
40-59 🟡 Medium Good match, minor differences
20-39 🟠 Low Partial match, review needed
0-19 🔴 Not Found No suitable rate found

Scoring factors:

  • Has price in database (+30)
  • Has resources breakdown (+25)
  • Unit matches expected (+20)
  • Material keywords match (+15)
  • Work type keywords match (+10)
  • Vector similarity >0.5 (+10)

Notes & Tips

  • Best photo angles: Capture full room, include reference objects (doors, sockets)
  • Renovation mode: AI automatically adds demolition works
  • Validation warnings: Check if <50% rates found — may need manual additions
  • Rate accuracy: Depends on DDC CWICR coverage for your region
  • Extend: Chain with PDF generation, email delivery, or CRM integration

Categories

AI · Data Extraction · Document Ops · Files & Storage

Tags

photo-analysis, gpt-4-vision, construction, cost-estimation, qdrant, vector-search, form-trigger, html-report, multilingual

Author

DataDrivenConstruction.io
https://DataDrivenConstruction.io
info@datadrivenconstruction.io

Consulting & Training

We help construction, engineering, and technology firms implement:

  • AI-powered visual estimation systems
  • CAD/BIM data processing pipelines
  • Vector database integration for construction data
  • Multilingual cost database solutions

Contact us to test with your data or adapt to your project requirements.

Resources

⭐ Star us on GitHub! github.com/datadrivenconstruction/DDC-CWICR