AI detection + humanizer workflow

Search engines and platforms are getting increasingly sensitive to AI-typical patterns: uniform sentence lengths, "It's important to note", over-structured lists. Rankion gives you two tools — an AI detector that scans text for AI probability, and a humanizer that actively makes it more natural.

Single-shot detection

Quick check for a single piece of text (e.g. a freshly written paragraph or an article delivered by a client):

curl -X POST https://rankion.ai/api/v1/ai-scanner/detect \
  -H "Authorization: Bearer YOUR_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"text": "It is important to note that artificial intelligence..."}'

Cost: 2 credits. The response gives you an ai_probability (0–100) and a sentence-level heatmap showing which sentences look particularly AI-typical.

From ai_probability ≥ 70 you should humanize. Below 40 is usually fine.

Article humanizer

If you want to push a complete article (e.g. a freshly generated one from the AI Content Editor) through the humanizer:

curl -X POST https://rankion.ai/api/v1/ai-scanner/humanize \
  -H "Authorization: Bearer YOUR_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "text": "Your full article text here...",
    "tone": "natural",
    "language": "en"
  }'

Cost: 5 credits. Synchronous, responds directly with the rewritten text. Duration: 5–15 seconds.

The humanizer varies sentence lengths, builds in imperfections (short sentences, question marks, inversions), swaps typical LLM filler phrases for everyday wording — and stays semantically faithful.

Bulk humanizer (async + batch polling)

For larger volumes (10+ articles, full content pipelines) there's the asynchronous bulk humanizer:

# Start a batch:
curl -X POST https://rankion.ai/api/v1/humanize \
  -H "Authorization: Bearer YOUR_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "texts": [
      {"id": "art-1", "content": "..."},
      {"id": "art-2", "content": "..."},
      {"id": "art-3", "content": "..."}
    ],
    "tone": "natural"
  }'

Cost: 8 credits per text. Response: HTTP 202 with a batch_id.

Then you poll:

curl https://rankion.ai/api/v1/humanize/{batch_id} \
  -H "Authorization: Bearer YOUR_TOKEN"

As long as status: "processing", it's still running. On status: "completed", results[] is populated with the humanized versions per input ID. Typical runtime: 30 seconds to 5 minutes depending on batch size.

When to use — when not

Use it when:

• The article comes straight from the AI Content Editor and needs to be publish-ready on money pages
• Texts are submitted to platforms with AI detection (universities, some marketplaces)
• You want to build a content series with a consistently natural voice

Don't use it when:

• The text has already been manually edited — the humanizer can introduce style breaks
• The content is heavily technical / factual (code, numbers, definitions) — the humanizer can loosen things that shouldn't be loosened
• The tone should be "expert / formal" — the humanizer default leans towards colloquial

Quality gate before publish

Recommended workflow for a final article:

1. Generate (Your first article with the AI Content Editor)
2. Score & optimize (Optimize content for Google + AI)
3. AI detection — check ai_probability
4. If ≥ 70 → humanize
5. Re-detection → must be < 40
6. Manual final edit (5 minutes is usually enough)
7. Publish

Module details and limits in AI Detector and Humanizer. API reference: AI Tools API (Detector + Humanizer).