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Enrich property inventory survey with image recognition and AI agent

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Enrich property inventory survey with image recognition and AI agent preview
Open on n8n.io

Important notice

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

1. Workflow Overview

This n8n workflow assists property managers and surveyors by reducing the time and effort it takes to complete property inventory surveys. In such surveys, articles and goods within a property may ...

Best for

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

Tools used

n8n-nodes-base.manualtrigger, @n8n/n8n-nodes-langchain.lmchatopenai, n8n-nodes-base.airtable, n8n-nodes-base.executeworkflowtrigger, n8n-nodes-base.set, n8n-nodes-base.httprequest, @n8n/n8n-nodes-langchain.toolworkflow, n8n-nodes-base.if

Source and attribution

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

Original n8n.io source

1.1 Workflow description

Title
Enrich property inventory survey with image recognition and AI agent
Workflow name
Enrich property inventory survey with image recognition and AI agent

This n8n workflow assists property managers and surveyors by reducing the time and effort it takes to complete property inventory surveys.

In such surveys, articles and goods within a property may need to be captured and reported as a matter of record. This can take a sizable amount of time if the property or number of items is big enough.

Our solution is to delegate this task to a capable AI Agent who can identify and fill out the details of each item automatically.

How it works

  • An AirTable Base is used to capture just the image of an item within the property
  • Our workflow monitoring this AirTable Base sends the photo to an AI image recognition model to describe the item for purpose of identification.
  • Our AI agent uses this description and the help of Google's reverse image search in an attempt to find an online product page for the item.
  • If found, the product page is scraped for the item's specifications which are then used to fill out the rest of the details of the item in our Airtable.

Requirements

  • Airtable for capturing photos and product information
  • OpenAI account to for image recognition service and AI for agent
  • SerpAPI account for google reverse image search.
  • Firecrawl.dev account for webspacing.

Customising this workflow

Try building an internal inventory database to query and integrate into the workflow. This could save on costs by avoiding fetching new each time for common items.

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 - When clicking "Test workflow"

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

Block 2 - OpenAI Chat Model1

Type / Role
@n8n/n8n-nodes-langchain.lmChatOpenAi - lmChatOpenAi
Config choices
Version 1

Block 3 - Get Applicable Rows

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

Block 4 - Execute Workflow Trigger

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

Block 5 - Edit Fields

Type / Role
n8n-nodes-base.set - set
Config choices
Version 3.3

Block 6 - Fallback Response

Type / Role
n8n-nodes-base.set - set
Config choices
Version 3.3

Block 7 - SERP Google Reverse Image API

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

Block 8 - Reverse Image Search Response

Type / Role
n8n-nodes-base.set - set
Config choices
Version 3.3

Block 9 - Reverse Image Search Tool

Type / Role
@n8n/n8n-nodes-langchain.toolWorkflow - toolWorkflow
Config choices
Version 1.1

Block 10 - Firecrawl Scrape API

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

Block 11 - Scrape Success?

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

Block 12 - Firecrawl Scrape Success Response

Type / Role
n8n-nodes-base.set - set
Config choices
Version 3.3

Block 13 - Firecrawl scrape Error Response

Type / Role
n8n-nodes-base.set - set
Config choices
Version 3.3

Block 14 - Firecrawl Web Scaper Tool

Type / Role
@n8n/n8n-nodes-langchain.toolWorkflow - toolWorkflow
Config choices
Version 1.1

Block 15 - Structured Output Parser

Type / Role
@n8n/n8n-nodes-langchain.outputParserStructured - outputParserStructured
Config choices
Version 1.1

Block 16 - Sticky Note

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

Block 17 - Sticky Note1

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

Block 18 - Sticky Note2

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

Block 19 - Sticky Note3

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

Block 20 - Sticky Note4

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

Block 21 - Enrich Product Rows

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

Block 22 - Sticky Note6

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

Block 23 - Analyse Image

Type / Role
@n8n/n8n-nodes-langchain.openAi - openAi
Config choices
Version 1.3

Block 24 - Object Identifier Agent

Type / Role
@n8n/n8n-nodes-langchain.agent - agent
Config choices
Version 1.5

Showing the first 24 of 29 workflow blocks. Download the JSON for the full node graph.

3. Summary Table

Workflow Enrich property inventory survey with image recognition and AI agent
Complexity advanced
Nodes 29
Categories Document Extraction, Multimodal AI
Author Jimleuk
Published 10 Jul 2024

4. Reproducing the Workflow from Scratch

  1. 1. Download the workflow JSON

    Use the JSON export at /data/workflows/2330/2330.json as the source template for this automation.

  2. 2. Import the template into n8n

    Open n8n, import the downloaded JSON, and review each node before activating the workflow.

  3. 3. Configure credentials and variables

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

  4. 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. 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.

Frequently asked questions

What does Enrich property inventory survey with image recognition and AI agent do?

This n8n workflow assists property managers and surveyors by reducing the time and effort it takes to complete property inventory surveys. In such surveys, articles and goods within a property may ...

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, Multimodal AI use case.