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Being able to manage the data and information within a company’s infrastructure is critical for properly assessing when sensitive information is either being mismanaged or to report an “all clear” when company policies are being followed as intended.

The landscape of data protection and privacy has undergone significant transformations worldwide, with Quebec’s Law25 emerging as a pivotal legislative piece within Canada.

Tokenization is an increasingly popular method used in data security, especially in areas that require the handling of sensitive data like financial transactions. But what exactly is tokenization, and how does it bolster data protection?

The European Union’s General Data Protection Regulation (GDPR) regulates what kind of processing is permitted that involves “special categories of data,” which includes race, origin, religious belief, and health data, among others.

Private AI, a leading provider of data privacy solutions, has introduced a Cloud API for its cutting-edge PII detection, redaction, and data minimization solution. This innovative tool is set to transform how businesses safeguard and manage sensitive customer data.

End-to-end privacy management refers to the process of protecting sensitive data throughout its entire lifecycle, from the moment it is collected to the point where it is destroyed.

The evolving landscape of data protection in Canada sees provinces enacting or refining their respective privacy legislations to address the challenges of the digital age.

At Private AI, we pride ourselves on making scalable solutions for large companies, small businesses, and government institutions that need to securely handle the potentially sensitive data and information that is flowing through their infrastructure.

Generative AI has become a cornerstone of modern technology, with potential applications ranging from content creation and customer service to scientific research and healthcare.

This last part of our series gets a bit more technical when discussing attacks on AI Models with the goal of obtaining illicit access to the data, as well as re-identification attacks launched against the data used by AI developers to train the model.

Despite the promising signs of AI used in healthcare that we explored in Part 1 of this series, ethical concerns persist regarding the potential misuse of these innovations and safeguarding health data.

AI is revolutionizing medicine by venturing into uncharted territories and addressing significant global healthcare challenges.

Data lakes are messy with vast amounts of data scattered everywhere as they serve as repositories for a myriad of structured and unstructured data.

About a year ago we covered the 2022 Cost of a Data Breach Report by IBM. The 2022 report had surfaced that the cost was highest in the healthcare and financial industry, followed by pharmaceuticals and technology.

In today’s data-driven landscape, the use of AI-based solutions, such as ChatGPT, has become increasingly prevalent.

Hello, dear community! We continue to see exciting improvements released since 3.7. Here is a synopsis of highlights from the version 3.8 updates release.

Data leaks are a serious threat to any business, and particularly those handling sensitive personal information, such as customer’s financial or health records.

New York State has taken a step towards ensuring responsible and ethical use of Artificial Intelligence (AI) technologies in the public sector through its newly established Acceptable Use of Artificial Intelligence Technologies policy.