Use cases
TextWatermarking hides a short payload in any text without changing what people see, and reads it back later. The pages below show what that is useful for, who it is for, the code to add it to an existing workflow, what it costs and where it stops working.
AI app and agent builders
Label AI-generated text at the source
An invisible label on every response, streamed or not, so you can tell later which response a text came from.
Agent builders
Let your agents sign what they write
Reports and emails signed with your channel key; verify origin and unchanged words before trusting them.
Publishers and companies
Trace a leaked document to its recipient
Identical-looking copies with an encrypted recipient id; read the id from a leaked copy.
Writers, agencies, legal teams
Prove authorship and detect edits
Stamp owner, date and a fingerprint of the words; a check says unchanged, edited, cut short or not yours.
Educators and learning platforms
Show where AI tutor answers end up
Label tutor answers and find them in submissions, with rules for using the result fairly.
Which mode do I need?
| You want | Mode and endpoint | Minimum text length | Who can read the payload |
|---|---|---|---|
| A label inside a streamed response | Plain tokens, /tokens | none: insert after the first character | anyone with an API token |
| A label on a finished text | Plain, /encode | a few characters | anyone with an API token |
| A private id or a signature | Keyed: /encode with a channel-bound token | (payload bytes + 30) × 8 | only tokens on your channel |
| To know when a text was cut short or damaged | Robust: /encode-robust (keyed or plain) | (payload bytes + 3) × 8; keyed (payload bytes + 30) × 8 | plain: anyone with a token; keyed: your channel |
Keep plain payloads opaque (an id that only means something in your own system), because any TextWatermarking user can read them. Signing channels are part of the Starter and Pro plans.
What holds for every use case
- The mark survives copy and paste between apps, chat and email. Text added after it does no harm.
- Rewriting, translation, retyping, OCR, screenshots and Unicode normalization remove it, as does any tool or exporter that strips invisible characters. Test your own pipeline.
- It is not an AI detector: a missing mark proves nothing about who or what wrote a text.
- Each mark and each found payload costs 1 credit. Checks that find nothing are free, and so are refused requests.
Frequently asked questions
What does TextWatermarking add to a text?
What survives and what does not?
Is it an AI detector?
What does a check cost when nothing is found?
Start building
- Quickstart: account, token and first call in five minutes
- MCP guide: connect Claude, Cursor and other clients
- API endpoints: every request and response field