Reality AI Inc. Raised $2.6M to verify trust in the AI era.

Documentation

API reference & integration guides

Everything you need to integrate image detection into your application. RESTful API, sub-second response times, and forensic-grade analysis.

API example

Detect in one request

curl -X POST https://api.realityai.ai/v2/detect \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: multipart/form-data" \
  -F "[email protected]"

# Response
{
  "verdict": "ai_generated",
  "confidence": 0.94,
  "models": {
    "gan_detection": { "score": 0.97, "label": "ai_generated" },
    "metadata_forensics": { "score": 0.89, "label": "anomalous" },
    "noise_analysis": { "score": 0.92, "label": "synthetic" },
    "c2pa_verification": { "status": "no_credentials" },
    "reverse_lookup": { "matches": 0 },
    "pattern_recognition": { "score": 0.95, "label": "ai_generated" }
  },
  "processing_time_ms": 1847
}
Integration guides

Common workflows

Single image detection

Submit an image and get a synchronous forensic report with confidence scores across six detection models.

Batch scanning

Process entire libraries asynchronously. Submit up to 1,000 images per batch with webhook notifications on completion.

Reading forensic reports

Understand the response schema: verdicts, confidence scores, model-level breakdowns, and metadata analysis.