Private AI 4.0: Your Data’s Potential, Protected and Unlocked

Share This Post

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 and securely to improve patient outcomes, accelerate research, and drive operational efficiency.

Preserve Data Relationships While Protecting Patient Privacy

One of the most significant challenges I’ve seen in privacy-preserving AI has been retaining meaningful context and relationships. I’ve heard from so many of you about the frustration of losing critical connections between entities in your data. With the introduction of our Coreference Resolution system, Private AI 4.0 tackles this complexity head-on by intelligently identifying references like “Dr. Smith,” “Jane Smith, MD,” and “Dr. J. Smith” as the same individual. This ensures that critical relationships are preserved, enabling richer, context-aware insights that drive improved clinical decision-making and research outcomes — all while adhering to stringent privacy standards.

Experiment Safely, Deploy with Confidence

When working with sensitive data, I understand how daunting it can be to experiment and test configurations without risking exposure. That’s why we are introducing our Container Playground in Private AI 4.0. It provides healthcare enterprises with a secure sandbox environment to refine data redaction settings, simulate compliance scenarios, and safely navigate unstructured data transformation. By mitigating the risk of data exposure, this feature empowers teams to transition seamlessly from testing to implementation with confidence, accelerating the adoption of privacy-preserving technologies in clinical and patient-driven environments.

Protect Intellectual Property in Collaborative Research

We’ve all seen how large language models (LLMs) continue to grow in popularity, and we’re just as dedicated to protecting your corporate secrets as we are to protecting personal data. Our Confidential Company Information (CCI) Detection and Redaction feature in Private AI 4.0 prevents unintended disclosure of proprietary research data during partnerships or clinical studies, addressing the growing need for privacy in collaborative research-driven environments.

Precision-Driven Privacy and Compliance

Precision is at the heart of everything we do, and Private AI 4.0 takes this to the next level with our Named Entity Recognition (NER) feature. This technology enables precise identification and protection of sensitive information across multiple languages and formats. It automatically structures unstructured data, reducing manual effort, enhances efficiency, and supporting global research initiatives while ensuring seamless privacy compliance. We’ve also introduced Checksum Validation, which uses algorithms like the Luhn check to verify the validity of credit card numbers and Social Security Numbers in structured or unstructured datasets. This feature not only ensures the integrity of patient data but also reinforces compliance with privacy regulations—another way we’re helping you stay ahead in an ever-changing regulatory landscape.

Unlock Data Access Like Never Before With Uncompromising Privacy. Welcome to Private AI 4.0

At Private AI, we believe that data privacy should not be a barrier to innovation—it should be a catalyst for it. With Private AI 4.0, healthcare organizations can confidently harness the full potential of their unstructured data, empowering them to make better decisions, improve outcomes, and drive progress. Designed to evolve alongside your privacy needs, we support you at every stage, from basic data minimization, to HIPAA compliant de-identification, and to expanding governance systems of your unstructured.

Private AI 4.0 represents the culmination of dedicated teamwork across engineering, data, product, design, and customer success teams. Under Kory Fong’s leadership, countless hours have been spent fine-tuning models, optimizing deployment workflows, and designing an intuitive user experience, and this release underscores the strength of our collaboration in delivering solutions.

Request a Demo to see how Private AI 4.0 can help your organization drive breakthrough innovation while protecting sensitive data.

Subscribe To Our Newsletter

Sign up for Private AI’s mailing list to stay up to date with more fresh content, upcoming events, company news, and more! 

More To Explore

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.