Classify & extract data from floorplans with Mistral AI OCR & JigsawStack

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Important notice

This workflow is provided as-is. Please review and test before using in production.

1. Workflow Overview

What it Does This workflow automatically classifies uploaded files (PDFs or images) as floorplans or non‑floorplans . It filters out j...

Best for

Document Extraction automation workflows
AI Summarization automation workflows
advanced n8n builders looking for reusable templates

Tools used

n8n-nodes-base.stickynote, n8n-nodes-base.if, n8n-nodes-base.webhook, n8n-nodes-base.respondtowebhook, n8n-nodes-base.code, n8n-nodes-base.extractfromfile, n8n-nodes-base.switch, n8n-nodes-base.httprequest

Source and attribution

This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by Stephan Koning.

Original n8n.io source

1.1 Workflow description

Title: Classify & extract data from floorplans with Mistral AI OCR & JigsawStack
Workflow name: Classify & extract data from floorplans with Mistral AI OCR & JigsawStack

🌊 What it Does

This workflow automatically classifies uploaded files (PDFs or images) as floorplans or non‑floorplans. It filters out junk files, then analyzes valid floorplans to extract room sizes and measurements.

👥 Who it’s For

Built for real estate platforms, property managers, and automation builders who need a trustworthy way to detect invalid uploads while quickly turning true floorplans into structured, reusable data.

⚙️ How it Works

User uploads a file (PDF, JPG, PNG, etc.).
Workflow routes the file based on type for specialized processing.
A two‑layer quality check is applied using heuristics and AI classification.
A confidence score determines if the file is a valid floorplan.
Valid floorplans are passed to a powerful OCR/AI for deep analysis.
Results are returned as JSON and a user-friendly HTML table.

🧠 The Technology Behind the Demo

This MVP is a glimpse into a more advanced commercial system. It runs on a custom n8n workflow that leverages Mistral AI's latest OCR technology. Here’s what makes it powerful:

Structured Data Extraction: The AI is forced to return data in a clean, predictable JSON Schema. This isn't just text scraping; it’s a reliable data pipeline.
Intelligent Data Enrichment: The workflow doesn't just extract data—it enriches it. A custom script automatically calculates crucial metrics like wall surface area from the floor dimensions, even using fallback estimates if needed.
Automated Aggregation: It goes beyond individual rooms by automatically calculating totals per floor level and per room type, providing immediate, actionable insights.

While this demo shows the core classification and measurement (Step 1), the full commercial version includes Step 2 & 3 (Automated Offer Generation), currently in use by a client in the construction industry.

Test the Live MVP

📋 Requirements

Jigsaw Stack API Key
n8n Instance
Webhook Endpoint

🎨 Customization

Adjust thresholds, fine‑tune heuristics, or swap OCR providers to better match your business needs and downstream integrations.

1.2 Logical Blocks

This catalog entry is organized from the workflow JSON. The node-level section below shows the executable blocks available for review before importing the template.

2. Block-by-Block Analysis

Block 1 - Low Quality Endpoint Note

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 2 - Manual Review Note

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 3 - Continue to JIG Note

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 4 - Classification Success Note

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 5 - Flow Summary Note

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 6 - File Limit Note

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 7 - 📘 Workflow Documentation

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 8 - Check – GDPR Consent

Type / Role: n8n-nodes-base.if - if
Config choices: Version 2.2

Block 9 - Webhook – Receive Upload

Type / Role: n8n-nodes-base.webhook - webhook
Config choices: Version 2

Block 10 - Respond – Consent Required

Type / Role: n8n-nodes-base.respondToWebhook - respondToWebhook
Config choices: Version 1.1

Block 11 - Process – Multiple File Uploads

Type / Role: n8n-nodes-base.code - code
Config choices: Version 2

Block 12 - Check – File Type (PDF/Image)

Type / Role: n8n-nodes-base.if - if
Config choices: Version 2.2

Block 13 - Extract – PDF Metadata/Text

Type / Role: n8n-nodes-base.extractFromFile - extractFromFile
Config choices: Version 1

Block 14 - Check – File Size & Pages

Type / Role: n8n-nodes-base.if - if
Config choices: Version 2.2

Block 15 - Analyze – Confidence Score (Heuristics)

Type / Role: n8n-nodes-base.code - code
Config choices: Version 2

Block 16 - Route – Confidence Levels

Type / Role: n8n-nodes-base.switch - switch
Config choices: Version 3.2

Block 17 - Respond – Low Quality/Drop

Type / Role: n8n-nodes-base.respondToWebhook - respondToWebhook
Config choices: Version 1.1

Block 18 - Classify – Image Files

Type / Role: n8n-nodes-base.httpRequest - httpRequest
Config choices: Version 4.2

Block 19 - Classify – PDF Text

Type / Role: n8n-nodes-base.httpRequest - httpRequest
Config choices: Version 4.2

Block 20 - Respond – Classification Result (Image)

Type / Role: n8n-nodes-base.respondToWebhook - respondToWebhook
Config choices: Version 1.1

Block 21 - Respond – Classification Result (PDF)

Type / Role: n8n-nodes-base.respondToWebhook - respondToWebhook
Config choices: Version 1.1

Block 22 - Respond – File Too Large

Type / Role: n8n-nodes-base.respondToWebhook - respondToWebhook
Config choices: Version 1.1

Block 23 - Upload – JigsawStack (Storage)

Type / Role: n8n-nodes-base.httpRequest - httpRequest
Config choices: Version 4.2

Block 24 - No Operation, do nothing

Type / Role: n8n-nodes-base.noOp - noOp
Config choices: Version 1

3. Summary Table

Workflow	Classify & extract data from floorplans with Mistral AI OCR & JigsawStack
Complexity	advanced
Nodes	24
Categories	Document Extraction, AI Summarization
Author	Stephan Koning
Published	09 Sept 2025

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

Use the JSON export at /data/workflows/8420/8420.json as the source template for this automation.
2. Import the template into n8n

Open n8n, import the downloaded JSON, and review each node before activating the workflow.
3. Configure credentials and variables

Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.
4. Test with sample data

Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.
5. Activate and monitor

Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.

5. General Notes & Resources

Review imported nodes carefully before activation. This catalog entry is intended to help you inspect the workflow structure, understand required services, and find related templates faster.

Node names, credentials, schedules, webhook paths, and external service limits may need adjustment for your workspace.

Download workflow JSON Original n8n.io source Document Extraction workflows AI Summarization workflows

Frequently asked questions

What does Classify & extract data from floorplans with Mistral AI OCR & JigsawStack do?

What it Does This workflow automatically classifies uploaded files (PDFs or images) as floorplans or non‑floorplans . It filters out j...

What do I need before importing this workflow?

Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.

Can I customize this workflow?

Yes. Use the block-by-block analysis and the downloadable JSON to inspect each node, then adjust credentials, prompts, schedules, filters, or destinations for your Document Extraction, AI Summarization use case.

Stephan Koning

15 workflows

Nodes

n8n-nodes-base.stickynote n8n-nodes-base.if n8n-nodes-base.webhook n8n-nodes-base.respondtowebhook n8n-nodes-base.code n8n-nodes-base.extractfromfile n8n-nodes-base.switch n8n-nodes-base.httprequest

Complexity

advanced

Published 09 Sept 2025

Likes 0

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Install path: /data/workflows/8420/8420.json

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Classify & extract data from floorplans with Mistral AI OCR & JigsawStack

Workflow preview

Important notice

1. Workflow Overview

Best for

Tools used

Source and attribution

1.1 Workflow description

🌊 What it Does

👥 Who it’s For

⚙️ How it Works

🧠 The Technology Behind the Demo

📋 Requirements

🎨 Customization

1.2 Logical Blocks

2. Block-by-Block Analysis

Block 1 - Low Quality Endpoint Note

Block 2 - Manual Review Note

Block 3 - Continue to JIG Note

Block 4 - Classification Success Note

Block 5 - Flow Summary Note

Block 6 - File Limit Note

Block 7 - 📘 Workflow Documentation

Block 8 - Check – GDPR Consent

Block 9 - Webhook – Receive Upload

Block 10 - Respond – Consent Required

Block 11 - Process – Multiple File Uploads

Block 12 - Check – File Type (PDF/Image)

Block 13 - Extract – PDF Metadata/Text

Block 14 - Check – File Size & Pages

Block 15 - Analyze – Confidence Score (Heuristics)

Block 16 - Route – Confidence Levels

Block 17 - Respond – Low Quality/Drop

Block 18 - Classify – Image Files

Block 19 - Classify – PDF Text

Block 20 - Respond – Classification Result (Image)

Block 21 - Respond – Classification Result (PDF)

Block 22 - Respond – File Too Large

Block 23 - Upload – JigsawStack (Storage)

Block 24 - No Operation, do nothing

3. Summary Table

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

2. Import the template into n8n

3. Configure credentials and variables

4. Test with sample data

5. Activate and monitor

5. General Notes & Resources

Frequently asked questions