Enrich Property Inventory Image Recognition
Upload a photo to Airtable and the agent identifies the item via image search then fills in its specs automatically.
What it does
Upload your property inventory photos to Airtable, and this agent automatically identifies each item and fills in its full specifications. It searches online product pages using image recognition, scrapes the details, and updates your records so you never have to manually type out specs again.
Step by step
- Configure an Airtable trigger to fire on new or updated records containing image fields.
- Send the image URL and a system prompt to OpenAI's Chat Completions API for initial item description.
- Pass the generated text and original image URL to SerpAPI using the 'reverse_image_search' parameter.
- Iterate through top search results, extract URLs, and send them to Firecrawl.dev for structured data extraction.
Where the LLM does the work
- Craft a detailed system prompt that instructs the model to identify specific product attributes like brand, model number, and material composition.
- Analyze the raw scraped HTML or JSON from Firecrawl to filter out irrelevant noise and extract only relevant specification fields for the Airtable schema.
- Generate a concise summary of the item's condition and features based on both the visual description and the technical specs found online.
Watch out for
SerpAPI reverse image search may return unrelated results if the photo is low quality, so implement a confidence threshold check before scraping.
Airtable has field size limits for rich text fields, truncate long descriptions to prevent record update failures.
Reverse image search often returns generic category pages instead of specific product pages, so validate that the scraped data matches the original item's key identifiers.
Tools that fit
OpenAI Chat Model LLM Image recognition to describe items
SerpAPI API Google reverse image search for product identification
Firecrawl.dev Service Scraping product specifications from web pages
The agent brief
Everything your agent needs, including the gotchas. Copy it and go.
You are helping me build the following AI agent workflow. ## Goal Enrich Property Inventory Image Recognition: Upload a photo to Airtable and the agent identifies the item via image search then fills in its specs automatically. ## Specification - What it does: Upload your property inventory photos to Airtable, and this agent automatically identifies each item and fills in its full specifications. It searches online product pages using image recognition, scrapes the details, and updates your records so you never have to manually type out specs again. - Trigger: Triggered by an event (Event · on new Airtable record) - Autonomy: Fully hands-off - Expected setup effort: about an afternoon - Tools/services involved: - Airtable: Storing property images and inventory data - OpenAI Chat Model: Image recognition to describe items - SerpAPI: Google reverse image search for product identification - Firecrawl.dev: Scraping product specifications from web pages ## Known pitfalls, handle each one explicitly in your implementation 1. SerpAPI reverse image search may return unrelated results if the photo is low quality, so implement a confidence threshold check before scraping. 2. Airtable has field size limits for rich text fields, truncate long descriptions to prevent record update failures. 3. Reverse image search often returns generic category pages instead of specific product pages, so validate that the scraped data matches the original item's key identifiers. ## Reference implementation https://n8n.io/workflows/2330 (workflow template) Fetch and inspect this before building. If it matches my stack, adapt it; if not, rebuild the pattern with my tools. ## Process requirements 1. Before building: ask me which of the listed tools I actually use and what my platform is (n8n / Make / code / other). Do not assume. 2. Adapt the pattern to my answers; do not force the reference stack. 3. Address every pitfall above; tell me how you handled each. 4. Provide a test plan I can run before letting this touch real data. 5. Ask before any step that sends messages, modifies data, or spends money. Source: https://usecasesforagents.com/use-case/enrich-property-inventory-with-ai-image-recognition/ via usecasesforagents.com
Frequently asked questions
Can I use a different Spreadsheet than Airtable?
Yes. Airtable is only the example spreadsheet in this recipe. The same flow works with Baserow, Excel and Google Sheets. Swap the spreadsheet connection and keep the rest of the setup as written.
Want this running in your business?
This is what I do. I design and build AI agents like this one, and keep them running. If you want it set up for your team instead of doing it yourself, get in touch.
Who it's for
Also fits Real Estate.