Company
Founded in Switzerland.
Artificial Intelligence Suisse SA, PO 280, Delemont, Switzerland.
Labeling for identification involves a detailed process of detecting and categorizing sensitive data entities within your text, ensuring clarity and organization.
The filtering of sensitive data is a meticulous de-identification process of replacing entities with placeholders, preserving the overall context and meaning.
Experience our tech magic in your browser! This playground downloads a prototype version of our model (~50MB), highlighting a selection of key entities for trial.
The dataset collection teams use to train stronger anonymization models, benchmark privacy performance, and expand multilingual coverage without starting from scratch.
Workflow
Train + eval
Coverage
Multilingual
Access
Open + enterprise
A better way to use AI with sensitive text. Personal data is masked in the browser before prompts are sent, so teams can move faster with less exposure.
Privacy
In-browser
Use
Daily work
Plans
Free + paid
Add PII detection, redaction, synthetic identities, and privacy-aware chat to your product without building the infrastructure yourself.
Format
REST
Entities
50+
Batch
3.5 GB
Run PII detection inside your own apps and workflows with Python and JavaScript packages built for local execution and direct control.
Runtime
Local
Packages
2
Actions
3 core
/ open standard · inspired by i18n & l10n
Most anonymization tools are proprietary, narrow, and impossible to compare. p5y is the open framework that translates personal and sensitive data into a shared privacy language.
Read the specOur dataset is proudly open-source, reflecting our commitment to raising awareness about privacy and giving back to the community with tools that are free for personal use.
You can find us on Hugging Face.