The best way to detect your content is to watermark it.
Our imperceptible watermarking technologies embed an unfalsifiable signal into every piece of AI-generated content, allowing you to prove its origin, authenticity, and traceability throughout its entire lifecycle.
Watermarking: the science of built-in traceability.
Watermarking enables native traceability of content.
It relies on the controlled injection of micro-signals at generation time, in the form of subtle modulations of the content’s statistical, spatial, or frequency components.
These variations create an origin signature, unique, unfalsifiable, and inseparable from its source.
Born from French and European public research, our watermark carries the legacy of fifteen years of scientific excellence.
Its reliability and robustness now set the standard for digital traceability technologies.
Watermarking, a modular
by design technology.
A multimodal watermark.
Designed from the ground up to be multimodal, our watermark applies to all forms of generation — text, image, audio, video, or code — with consistent precision and robustness.
Augmented watermarking
Watermarking is the most solid building block of traceability. Label4.ai promotes its use while integrating other complementary approaches whenever they enhance the system’s reliability or compliance.
A state-of-the-art watermark
Not all watermarks are created equal. Label4.ai builds on more than 15 years of research, setting a new reliability standard in digital traceability.
Watermarking your content means keeping control over your AI.
AI model providers, internally generated AI content, RAG workflows, sensitive documents…
With imperceptible watermarking, you embed an unfalsifiable signature into every piece of content, tied to its author, creation context, and the generative model used.
Ensure full traceability of your AI-generated content.
Strengthen the reliability of your brand and communications.
Integrate seamless traceability into your AI workflows.
Protect your digital assets against misuse and falsification.
Anticipate transparency requirements and demonstrate your commitment to responsible AI.
