HHS’ proposed HIPAA Amendment to Strengthen Cybersecurity in Healthcare and how Private AI can Support Compliance

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

Japan’s Health Data Anonymization Act: Enabling Large-Scale Health Research

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

What the International AI Safety Report 2025 has to say about Privacy Risks from General Purpose AI

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

How Private AI Facilitates GDPR Compliance for AI Models: Insights from the EDPB’s Latest Opinion

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

Enhancing Compliance with US Privacy Regulations for the Insurance Industry Using Private AI

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

Belgium’s Data Protection Authority on the Interplay of the EU AI Act and the GDPR

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

Navigating Compliance with Quebec’s Act Respecting Health and Social Services Information Through Private AI’s De-identification Technology

Quebec’s new Act Respecting Health and Social Services Information (ARHSSI) introduces a notable tightening of data privacy requirements within the province, with a distinct emphasis on safeguarding health and social services information.  The Act mandates that all information held by certain public bodies and potentially entrusted to third parties must remain confidential unless explicitly authorized … Read more

How Private AI Can Help to Comply with Thailand’s PDPA

Thailand’s Personal Data Protection Act (PDPA) was signed into law in 2019 and came into force in mid 2022. It is in many ways inspired by Europe’s General Data Protection Regulation (GDPR) but with some notable differences, e.g., potential prison time for violations in addition to criminal and administrative fines and a greater social good … Read more

How Private AI Can Help Financial Institutions Comply with OSFI Guidelines

The Office of the Superintendent of Financial Institutions (OSFI) has set forth guidelines to ensure that Federally Regulated Financial Institutions (FIs) maintain robust data security, risk management, and operational resilience. Private AI’s advanced machine learning and natural language processing technologies provide helpful tools that can help FRFIs meet these requirements efficiently and effectively. Since the … Read more

Download the Free Report

Request an API Key

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!

Language Packs

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

Rappel

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.

99.5%+ Accuracy

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.