Free tools to scan text for hidden watermark characters and strip EXIF, XMP, and C2PA metadata from images. Everything runs in your browser or on our stateless API, we store nothing. We do not claim to remove statistical token-level watermarks; that is not something any tool can do reliably.
From detection to removal to ongoing monitoring, our platform handles every aspect of AI watermark management for modern teams.
Scans text for hidden zero-width and invisible Unicode characters that are sometimes used as invisible watermarks, and reports exactly which ones it finds. Works on text from any source. It does not read statistical token-level watermarks, those require the model owner's private key.
Enterprise-grade removal preserves your original meaning, tone, and formatting while eliminating statistical watermark patterns. Side-by-side comparison shows exactly what changed.
Set up automated workflows to scan content pipelines in real time. Get alerts when watermarked content is detected, with integration support for Slack, email, and webhooks.
Three simple steps to detect and manage AI watermarks in your content.
Drop your text, code, or image into our scanner. We support bulk uploads via CSV, API, or direct paste for instant analysis across any content format.
Results come back in about a second and list the exact hidden characters found (name, code point, and count) so you can see precisely what is in your text. No made-up confidence percentages, just what is actually there.
Choose to remove detected watermarks instantly or set up continuous monitoring. All changes are tracked in an audit log for compliance and review purposes.
Start free, scale as you grow. No credit card required.
An AI watermark is a statistical pattern embedded in text, images, or code generated by AI models like Claude, GPT-4, and Gemini. These watermarks are invisible to the human eye but can be detected through statistical analysis. They are typically implemented by subtly biasing token selection during generation, creating patterns that are statistically unlikely in human-written content.
It reliably detects hidden Unicode characters, zero-width spaces, joiners, variation selectors, and tag characters, which are sometimes used as invisible text watermarks, and it strips EXIF, XMP, and C2PA metadata from images. It does NOT detect statistical token-level watermarks (the kind embedded in an AI model's word choice). Those require the model owner's private key and cannot be detected or removed reliably by any third-party tool. We would rather tell you that than sell you a number we made up.
The legality of watermark removal varies by jurisdiction and use case. In most contexts, modifying AI-generated text for your own use is permissible. However, removing watermarks to misrepresent AI content as human-written may violate platform terms of service or disclosure requirements. We recommend consulting your legal team for specific compliance questions.
No. The hidden-character scan and the image metadata stripping are model-agnostic, they work on any text or image regardless of which tool produced it, because they operate on the file itself, not on a model signature.