API for Writing Tools

ChatGPT API Adds Watermarks. Your Users Get Detected. Strip Them First.

Integrate invisible watermark removal into your AI writing tool. One endpoint protects all your users. 40+ watermark types removed in <100ms.

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const response = await fetch(
  "https://api.gptwatermarkremover.com/v1/clean",
  {
    method: "POST",
    headers: {
      "X-API-Key": "YOUR_API_KEY",
      "Content-Type": "application/json"
    },
    body: JSON.stringify({ text: "Your AI-generated text here" })
  }
);

const { cleaned_text } = await response.json();

The Watermark Problem

AI APIs embed invisible tracking characters. Your users copy the text. Detectors flag it. You lose users.

1. Your SaaS Calls ChatGPT

You use openai.chat.completions.create() to generate content for users.

2. Response Has Watermarks

ChatGPT embeds invisible Unicode characters (U+200B, U+00AD, etc.) as tracking markers.

3. Users Get Detected → Churn

User copies to Google Docs. AI detectors scan for watermarks. Content flagged. User leaves.

The Fix: Strip Watermarks Before Returning to Users

Add one API call between ChatGPT and your user: ChatGPT API → Watermark Removal API → Clean text to user. Text stays word-for-word identical. Only invisible tracking removed.

// Your SaaS calls ChatGPT API
const aiResponse = await openai.chat.completions.create({
  model: "gpt-4",
  messages: [{ role: "user", content: "Write an email..." }]
});
const aiText = aiResponse.choices[0].message.content; // Has watermarks!

// Strip watermarks before showing to user
const cleanResponse = await fetch(
  'https://api.gpt-watermark-remover.com/v1/remove',
  {
    method: 'POST',
    headers: { 'X-API-Key': 'your_api_key' },
    body: JSON.stringify({ text: aiText })
  }
);
const { clean_text } = await cleanResponse.json();

// Return clean text to user - no watermarks
return clean_text;  // ✅ Protected

Integration in 3 Steps

Add watermark removal to your existing AI workflow

1

Get API Key

Sign up, get your API key. 250 free calls to test integration.

2

Add Middleware Call

After ChatGPT responds, POST text to /v1/remove endpoint.

3

Return Clean Text

Show the clean_text field to users. No watermarks, no detection.

<100ms
Response Time
40+
Watermark Types
99.9%
Uptime SLA
100k
Max Chars/Request
99.9%
Uptime
<100ms
Response Time
All Known
Watermark Types
100K
Max Characters
HTTPS encrypted
No text stored
Edge-deployed globally

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  • 1,000 API calls per month
  • 100,000 characters per request
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Watermark Types We Detect

Our API detects and removes all known invisible Unicode characters used by AI systems like ChatGPT, Claude, Gemini, and others to watermark generated text.

Zero-Width Characters

Invisible characters with no visual width, commonly inserted by AI systems to mark generated text.

Zero-Width Space
Most common AI watermark. Invisible space character inserted between words or characters.
Zero-Width Non-Joiner
Prevents character joining in scripts like Arabic. Used as hidden marker in AI text.
Zero-Width Joiner
Forces character joining. Commonly used in emoji sequences, exploited for watermarking.
Byte Order Mark
Originally for encoding detection. When embedded mid-text, serves as invisible watermark.
Word Joiner
Prevents line breaks. Invisible character used to mark AI-generated content.

Formatting Characters

Characters that affect text rendering or spacing without being visible.

Soft Hyphen
Marks where a word can break. Invisible unless line breaks at that point.
Combining Grapheme Joiner
Affects how characters combine. Used to invisibly mark text.
Function Application
Mathematical invisible operator. Repurposed as text watermark.
Invisible Times
Mathematical multiplication marker. Zero-width, used in watermarking.
Invisible Separator
Mathematical separator with no width. Hidden text marker.

Bidirectional Control

Characters that control text direction, often invisible and exploitable for watermarking.

Left-to-Right Mark
Forces left-to-right text direction. Invisible directional override.
Right-to-Left Mark
Forces right-to-left text direction. Hidden directional marker.
Directional Embeddings
Multiple characters that embed text direction. Invisible formatting controls.
Directional Overrides
Override text direction rendering. Hidden watermark characters.

Variation Selectors

Characters that modify how preceding characters render, often invisibly.

Standard Variation Selectors
Selectors that change character appearance. Often invisible modifications.
Extended Variation Selectors
Extended selectors for specialized use. Rarely used, suspicious when found in regular text.

Annotation Characters

Characters for interlinear annotations, invisible in most contexts.

Annotation Anchor
Marks annotation start. Invisible formatting character.
Annotation Separator
Separates annotation elements. Zero-width marker.
Annotation Terminator
Ends annotation. Hidden text marker.

Why Do AI Systems Add Watermarks?

Large language models like ChatGPT, Claude, and Gemini embed invisible watermarks to enable detection of AI-generated content. These watermarks use Unicode characters that have zero visual width but can be detected programmatically. Our API removes all known watermark patterns while preserving your text's meaning and formatting.

Developer FAQ

Technical questions about API integration

Start protecting your users in under 5 minutes

Stop Losing Users to AI Detectors

Join developers protecting millions of users with invisible watermark removal. One endpoint. 1,000 free API calls. No credit card required.

<100ms
Response Time
40+
Watermark Types
99.9%
Uptime SLA
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In-Depth Guides

Watermark Removal vs AI Detection: What's the Difference?

AI watermark removal and AI content detection are two separate processes that address different parts of how large language models (LLMs) generate and mark text. Although both relate to identifying whether text was written by an AI system, they work in fundamentally different ways.

Read more: Watermark Removal vs AI D...

Why Short Texts Break AI Detection and Watermark Analysis

Short texts often cannot be reliably analyzed for AI detection or watermark identification because they lack the minimum amount of linguistic data required for statistical evaluation.

Read more: Why Short Texts Break AI ...