POST /v1/analyze

Analyzes tire and vehicle images using advanced AI to identify the vehicle's brand, model, year, trim levels, and tire specifications.

Endpoint

POST https://api.ruedalens.com/v1/analyze

Authentication

Requires a valid API key in the Authorization header.

Authorization: Bearer rdlns_sk_...

Request

Headers

Body Parameters

Example Request

curl -X POST https://api.ruedalens.com/v1/analyze \
  -H "Authorization: Bearer rdlns_sk_your_api_key_here" \
  -H "Content-Type: application/json" \
  -d '{
    "tireImage": "/9j/4AAQSkZJRg...",
    "carImage": "/9j/4AAQSkZJRg..."
  }'

Response

Success — 200 OK

{
  "success": true,
  "requestId": "cmlecazi4000111qu590n9v6i",
  "data": {
    "vehicles": [
      {
        "confidence": 0.98,
        "brand": "Lexus",
        "model": "NX",
        "trims": ["300h", "300"],
        "start_year": 2017,
        "end_year": 2021,
        "current_tire": {
          "width": 225,
          "aspect_ratio": 60,
          "diameter": 18,
          "load_index": "100",
          "speed_index": "H",
          "structure": "R",
          "runflat": null,
          "xl": null
        },
        "oe_front_tire": {
          "width": 225,
          "aspect_ratio": 60,
          "diameter": 18,
          "load_index": "100",
          "speed_index": "H",
          "structure": "R",
          "runflat": false,
          "xl": false
        },
        "oe_rear_tire": {
          "width": 225,
          "aspect_ratio": 60,
          "diameter": 18,
          "load_index": "100",
          "speed_index": "H",
          "structure": "R",
          "runflat": false,
          "xl": false
        },
        "pressure_front": 2.2,
        "pressure_rear": 2.2
      }
    ]
  },
  "metrics": {
    "executionTimeMs": 10364
  },
  "timestamp": "2026-02-08T22:54:03.962Z"
}

Response Fields

Tire Object Structure

Each tire object (current_tire, oe_front_tire, oe_rear_tire) contains:

Understanding the Tire Fields

The response includes three tire specifications that serve different purposes:

• current_tire: The tire specification read from the sidewall image via OCR. This is what's actually mounted on the vehicle. May contain null values if text isn't legible.
• oe_front_tire: The original equipment (OE) tire specification for the front axle from the manufacturer's database. This is what came from the factory.
• oe_rear_tire: The original equipment tire specification for the rear axle. For most vehicles, this matches the front tire unless the vehicle has a staggered setup.

Understanding Confidence Scores

The confidence field (0.0 to 1.0) indicates how certain the AI is about the vehicle identification:

Understanding Trims Array

The trims array is ordered by likelihood, with the most probable trim first:

"trims": ["300h", "300", "200t"]

This means the vehicle is most likely a "300h" trim, but could also be a "300" or "200t". Use the first trim for the most likely match.

Error Responses

400 Bad Request

{
  "success": false,
  "error": {
    "code": "INVALID_IMAGE",
    "message": "Invalid request body",
    "details": {
      "field": "tireImage",
      "issue": "Must be a valid base64-encoded image"
    }
  }
}

401 Unauthorized

{
  "success": false,
  "error": {
    "code": "INVALID_API_KEY",
    "message": "Invalid API key"
  }
}

429 Too Many Requests

Returned as RATE_LIMIT_EXCEEDED for burst rate limits, or QUOTA_EXCEEDED for monthly quota exhaustion (Sandbox plan):

{
  "success": false,
  "error": {
    "code": "QUOTA_EXCEEDED",
    "message": "Monthly quota exceeded"
  }
}

Image Requirements

Image Quality Guidelines

The quality of your input images directly affects accuracy. Follow these guidelines for best results:

Tire Image Best Practices

• Lighting: Ensure even lighting with no harsh shadows on the sidewall text
• Angle: Photograph perpendicular to the wheel (straight-on, not at an angle)
• Focus: Make sure all text on the sidewall is sharp and legible
• Coverage: Capture the entire tire size marking (e.g., "225/60 R18 100H")
• Avoid: Blurry images, extreme angles, heavy shadows, or obstructed text

Vehicle Image Best Practices

• Framing: Include the full vehicle in the shot (front three-quarter, side, or rear angles work best)
• Distance: Stand 10-15 feet away for optimal framing
• Clarity: Ensure the vehicle's body style and design elements are clearly visible
• Avoid: Extreme close-ups, partial vehicle shots, or heavily cropped images

Visual Examples

Below are real-world examples demonstrating proper image capture technique for optimal results.

Example 1: Standard Conditions

Tire image: Perpendicular angle, even lighting, all sidewall text legible

Vehicle image: Full view with clear body lines and design elements

Example 2: Challenging Conditions

Our system maintains high accuracy even with less-than-perfect conditions:

Muddy tire: Despite dirt and poor conditions, the system successfully extracts tire specifications

Vehicle image: Rugged conditions demonstrate robust recognition capabilities

Performance & Billing

Processing Time

Typical end-to-end response time: 7-15 seconds

This includes:

• Network time: Image upload to our servers (~1-3s depending on connection and image size)
• Server processing: AI analysis and enrichment (~7-10s)
• Network time: Response download (<1s)

Factors affecting processing time:

The executionTimeMs metric:

• Reflects server-side processing time only (excludes network time)
• Useful for monitoring API performance trends
• Typically ranges from 7,000ms to 12,000ms

Quota & Billing

• Each request counts toward your monthly quota, regardless of success or failure
• Multiple vehicle matches may be returned when confidence is distributed across similar models
• The API processes both images simultaneously for maximum accuracy