We’ve said it before, and we’ll say it again: healthcare data has the power to transform care. It can personalize treatments and speed up diagnoses in ways we’ve only dreamed of. But here’s the part nobody really likes to talk about: most healthcare data strategies fail before they even get off the ground. It’s not … Read more
The European Data Protection Board (EDPB) recently released its comprehensive Guidelines 01/2025 on Pseudonymisation, a document rich with practical insights into the application of pseudonymisation under the General Data Protection Regulation (GDPR). While pseudonymisation is often associated with the replacement of personal identifiers, the EDPB’s guidance makes it clear that achieving effective pseudonymisation requires more … Read more
On December 27, 2024, the U.S. Department of Health and Human Services (HHS), through its Office for Civil Rights (OCR), issued a proposed rule to enhance the cybersecurity measures required under the HIPAA Security Rule. This Notice of Proposed Rulemaking (NPRM) seeks to bolster the defenses of the U.S. healthcare system against the rising tide … Read more
Anonymized and pseudonymized medical data are at the heart of cutting-edge research and innovation in healthcare. By stripping away personal identifiers and adding additional privacy-preserving measures, these data allow for advanced studies without compromising the privacy of individuals. In Japan, as elsewhere, the path to leveraging this valuable resource has been complex due to the … Read more
As the world gears up for the AI Action Summit in Paris in February 2025, global policymakers, researchers, and industry leaders are turning their attention to a landmark publication: The International AI Safety Report 2025. This report, a collaborative effort by 96 AI experts from around the world, represents the most comprehensive scientific assessment to … Read more
I know first-hand how the enterprise data management landscape is evolving rapidly. Today, I’m thrilled to announce Private AI 4.0. This release redefines how healthcare businesses harness their unstructured data while maintaining fine-grained privacy controls and the highest standards of compliance. With Private AI 4.0, we are turning challenges into opportunities by enabling analytics confidently … Read more
The European Data Protection Board (EDPB) has recently provided critical guidance on ensuring GDPR compliance during the development and deployment of AI models. Opinion 28/2024 addresses core data protection issues, such as the use of personal data in AI model training, legal bases for processing, and the impact of unlawful data processing on the deployment … Read more
Artificial intelligence and large language models (LLMs) are transforming the way we work, and the boundaries of data privacy are being tested like never before. While most organizations have measures in place to secure their proprietary algorithms and internal data repositories, there’s a growing challenge that can’t be overlooked: the uncontrolled sharing of Confidential Company … Read more
The US insurance industry operates under a complex landscape of privacy laws and regulations designed to protect consumers’ personal information. At the heart of this regulatory framework are standards developed by the National Association of Insurance Commissioners (NAIC), alongside federal and state laws like the Gramm-Leach-Bliley Act (GLBA). Key NAIC model laws addressing privacy in … Read more
The Belgium Data Protection Authority’s recent report, Artificial Intelligence Systems and the GDPR: A Data Protection Perspective, is a timely analysis exploring the interplay of the General Data Protection Regulation (GDPR) and the EU Artificial Intelligence (AI) Act. It seeks to provide insights into where the EU AI Act adds additional compliance requirements to aspects … Read more
Fill out the form below and we’ll send you a free API key for 500 calls (approx. 50k words). No commitment, no credit card required!
Expand the categories below to see which languages are included within each language pack.
Note: English capabilities are automatically included within the Enterprise pricing tier.
French
Spanish
Portuguese
Arabic
Hebrew
Persian (Farsi)
Swahili
French
German
Italian
Portuguese
Russian
Spanish
Ukrainian
Belarusian
Bulgarian
Catalan
Croatian
Czech
Danish
Dutch
Estonian
Finnish
Greek
Hungarian
Icelandic
Latvian
Lithuanian
Luxembourgish
Polish
Romanian
Slovak
Slovenian
Swedish
Turkish
Hindi
Korean
Tagalog
Bengali
Burmese
Indonesian
Khmer
Japanese
Malay
Moldovan
Norwegian (Bokmål)
Punjabi
Tamil
Thai
Vietnamese
Mandarin (simplified)
Arabic
Belarusian
Bengali
Bulgarian
Burmese
Catalan
Croatian
Czech
Danish
Dutch
Estonian
Finnish
French
German
Greek
Hebrew
Hindi
Hungarian
Icelandic
Indonesian
Italian
Japanese
Khmer
Korean
Latvian
Lithuanian
Luxembourgish
Malay
Mandarin (simplified)
Moldovan
Norwegian (Bokmål)
Persian (Farsi)
Polish
Portuguese
Punjabi
Romanian
Russian
Slovak
Slovenian
Spanish
Swahili
Swedish
Tagalog
Tamil
Thai
Turkish
Ukrainian
Vietnamese
Testé sur un ensemble de données composé de données conversationnelles désordonnées contenant des informations de santé sensibles. Téléchargez notre livre blanc pour plus de détails, ainsi que nos performances en termes d’exactitude et de score F1, ou contactez-nous pour obtenir une copie du code d’évaluation.
Number quoted is the number of PII words missed as a fraction of total number of words. Computed on a 268 thousand word internal test dataset, comprising data from over 50 different sources, including web scrapes, emails and ASR transcripts.
Please contact us for a copy of the code used to compute these metrics, try it yourself here, or download our whitepaper.
