Patricia Graciano 
In This Blog Understanding PII in Review Data Privacy Legislation Impacting Review Data The Role of PII Redaction in Review APIs Implementing PII Redaction in Review Data Pipelines Why Privacy Matters in Leveraging Review Data User reviews have become a crucial element for businesses seeking to understand consumer sentiment, improve products, and build trust with … Read more
An independent evaluation has confirmed that Private AI’s Personal Identifying Information (PII) identification model is both highly effective and secure, now backed by Armilla AI’s Guaranteed Warranty and insurers Swiss Re, Greenlight Re and Chaucer. This validation addresses crucial concerns regarding the reliability and fairness of AI-driven privacy tools, providing assurance to organizations that their … Read more
AI has undoubtedly taken over the world, becoming an indispensable tool for companies looking to maintain a competitive edge. The global artificial intelligence market size was estimated at USD 196.63 billion in 2023 and is projected to grow at a CAGR of 36.6% from 2024 to 2030. From streamlining business operations to delivering personalized customer … Read more
ChatGPT took the world by storm, and companies everywhere are leveraging the OpenAI tool to streamline their processes, improve productivity, and enhance customer experience. But how much can we trust LLMs with business data? What are the biggest ChatGPT privacy concerns? How can we leverage the tool while maintaining privacy? We explore the answers. Just … 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.
