Add Container OCR to Your Lovable.dev App in 5 Minutes

The problem: Standard AI can't read vertical text on rusted steel

Tools like Lovable.dev are remarkable at generating apps — but they stop at the file boundary. You can build a beautiful freight tracking interface in minutes, yet the actual extraction of an 11-character container number from vertically stacked text on corrugated steel doors requires a dedicated Container OCR API. Standard vision models routinely fail to read text split across metal ridges or stacked top-to-bottom.

The solution: ISO 6346 precision, instantly

StructOCR's /v1/container endpoint accepts a photo and returns a clean JSON object with the validated ISO 6346 container number, instantly decoding the owner prefix, category, and check digit. Because it speaks plain HTTP, Lovable can wire it up from a single fetch call.

Integrate StructOCR in Lovable (3 Steps)

1. 1

   Create a Lovable project and describe your app

   Open lovable.dev and start a new project. In the chat box, describe the logistics tool you want to build — be specific about the scanning interface.

   💬Try this prompt: "Build a mobile-friendly yard management app. Users can upload a photo of shipping container doors, and the app will display the extracted container number, owner code, and check digit."
2. 2

   Tell Lovable to call the StructOCR API

   Once Lovable scaffolds the UI, paste the follow-up prompt below. Lovable will write the fetch call, handle the file upload, and wire the response to your UI components.

   💬Follow-up prompt: "When a user uploads an image, send it as a multipart/form-data POST to https://api.structocr.com/v1/container with an Authorization header containing my API key. Display the returned JSON fields in the results panel."

   // Lovable generates something like this — you just supply the key const response = await fetch('https://api.structocr.com/v1/container', { method: 'POST', headers: { Authorization: `Bearer ${import.meta.env.VITE_STRUCTOCR_KEY}` }, body: formData, });
3. 3

   Add your StructOCR API key and publish

   Go to Project Settings → Environment Variables in Lovable and add your StructOCR key. Then hit Publish. Your container scanner is live.

   💬Variable name: VITE_STRUCTOCR_KEY — get your free key at structocr.com/dashboard

   VITE_STRUCTOCR_KEY=sk_live_xxxxxxxxxxxxxxxx

What you can build in Lovable with this integration

• Gate automation app: Let truck drivers or gate inspectors snap a photo of the container to automatically log the entry/exit time and verify the container number against the manifest.
• Yard management system (YMS): Build a mobile app for yard jockeys to scan container numbers and update parking slot locations in real-time. A core feature of modern logistics automation.
• Freight forwarding tracker: Create a tool where warehouse staff scan containers during loading/unloading to generate instant status updates for end-customers.
• Damage inspection portal: Add an upload step to a container inspection flow: extract the container number automatically from the damage photos to link the evidence to the correct asset.

The prompt and the code

Copy the Lovable prompt into your project chat to generate the integration. The JavaScript tab shows what Lovable produces — useful if you want to verify or customize it.

Prerequisite: A free StructOCR account — get your API key at structocr.com/dashboard (no credit card required)

I need to add shipping container OCR to this app.

When a user uploads an image:
1. Send it as multipart/form-data to: POST https://api.structocr.com/v1/container
2. Include the header: Authorization: Bearer ${VITE_STRUCTOCR_KEY}
3. The response is JSON with fields: data.container_number, data.is_valid, data.parsed.owner_code, data.parsed.check_digit
4. Display the extracted container number and the decoded parts in the results panel
5. Show a loading spinner while the request is in flight
6. Show an error message if the upload fails

Use the environment variable VITE_STRUCTOCR_KEY for the API key.

What the API returns

Not just the raw string—the API automatically validates the check digit and breaks down the components. Your Lovable app can bind this directly to the UI.

{
  "success": true,
  "data": {
    "container_number": "ZCSU8921655",
    "is_valid": true,
    "confidence": "High",
    "parsed": {
      "owner_code": "ZCS",
      "category": "U",
      "serial_number": "892165",
      "check_digit": "5"
    }
  }
}