Navigating the New Frontier of Data Privacy: Protecting Confidential Company Information in the Age of AI

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

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

Unlocking New Levels of Accuracy in Privacy-Preserving AI with Co-Reference Resolution

Sign up for Private AI 4.0alpha and get early access to Coreference Resolution and more new features! Sign up now! In the fast-evolving world of AI, where data is at the core of decision-making, one challenge remains constant: ensuring appropriate privacy and protection of an individual’s and an organization’s data. That’s why, in May 2023, … 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

The American Privacy Rights Act – The Next Generation of Privacy Laws

For the longest time, the US was one notable outlier in the global trend of developing federal-level comprehensive privacy laws. The nation, (in)famous for its patchworked approach to privacy with many sector-specific and 15 (soon to be 17) states laws that cover privacy protection comprehensively, is now (once again) close to joining the other 137 … Read more

How Private AI Can Help with Compliance under China’s Personal Information Protection Law (PIPL)

China’s Personal Information Protection Law (PIPL) that come into force November 1, 2021 sets out stringent requirements for the handling, processing, and protection of personal information. Organizations operating under this law must navigate a complex landscape of obligations, including limiting data collection, ensuring data security, managing sensitive information, and responding to data breaches. Private AI’s … Read more

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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.