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

The problem: Standard AI can't read embossed fiberglass

Tools like Lovable.dev are remarkable at generating apps — but they stop at the file boundary. You can build a beautiful marina management interface in minutes, yet the actual extraction of a Hull Identification Number (HIN) from a reflective gel coat, painted-over metal plate, or weathered transom requires a dedicated HIN OCR API. Standard vision models routinely fail to distinguish shallow engravings from background noise.

The solution: Marine-grade precision and parsing

StructOCR's /v1/hin endpoint accepts a photo and returns a clean JSON object with the validated HIN, plus it automatically breaks down the code into the Manufacturer Identity Code (MIC), serial number, and production dates. 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 marine tool you want to build — be specific about the scanning interface.

   💬Try this prompt: "Build a mobile-friendly HIN scanner app. Users can upload a photo of a boat's transom, and the app will display the extracted HIN, manufacturer code, and production year."
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/hin 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/hin', { 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 HIN 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

• Boat dealership inventory: Let staff snap a photo of a vessel's transom to instantly log it into the inventory system, automatically decoding the model year and manufacturer without manual typing.
• Marine insurance claims: Add an upload step to a self-service claims flow: extract the HIN automatically from the policyholder's photos to verify the insured vessel. A perfect fit for marine automation.
• Marina & dock management: Build a mobile app for dockmasters to scan visiting boats to ensure they match registered tenant records and verify vessel age.
• Vessel registration portal: Create a tool that validates HIN formats on the fly for state or federal boat registration compliance.

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 HIN OCR to this app.

When a user uploads an image:
1. Send it as multipart/form-data to: POST https://api.structocr.com/v1/hin
2. Include the header: Authorization: Bearer ${VITE_STRUCTOCR_KEY}
3. The response is JSON with fields: data.hin_number, data.is_valid, data.parsed.manufacturer_code, data.parsed.model_year
4. Display the extracted HIN and the decoded manufacturer/year 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 decodes the manufacturer and production dates. Your Lovable app can bind this directly to the UI.

{
  "success": true,
  "data": {
    "hin_number": "US-TNPD7474B899",
    "is_valid": true,
    "validation_error": null,
    "confidence": "High",
    "parsed": {
      "country_code": "US",
      "manufacturer_code": "TNP",
      "serial_number": "D7474",
      "production_month": "February",
      "production_year_short": "8",
      "model_year": "1999"
    }
  }
}