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Patricia Thaine

We identify Personally Identifiable Information in data, enabling companies to protect their customers’ information while fully utilizing their data and complying with their data protection regulation obligations. See our overview video:

Tell us about yourself?

I have always been interested in technology and how it can enhance our lives, but I’m equally passionate about the need for data security and privacy, especially when it comes to personal information.

While doing grad studies in Computer Science at the University of Toronto, I met my Co-Founder/our CTO, Pieter Luitjens, an expert in the development and deployment of ML models in really low-resource environments. We discussed a number of business ideas over the years, and the issue of training data containing Personally Identifiable Information (PII) was often a roadblock in the creation of ML products. This led us to the idea of creating a “Privacy Layer for Software” that enables companies to fully utilise their data by first identifying and then protecting all their customers’ PII within their data, and so, Private AI was born.

If you could go back in time a year or two, what piece of advice would you give yourself?

Others can’t read your mind. Write everything down, even if you think it’s obvious, into quick explainers.

What problem does your business solve?

Data is one of the most valuable assets every business has. However, being able to use that data to analyse the success of your current business strategies and to design new products and strategies is difficult without risking breaching the privacy of your customers. Thus, most companies sit on their data but fail to properly protect or use it. Private AI can help them unlock the true value of their data while protecting the privacy of their customers’ personal information and meeting their data protection regulatory obligations.

What is the inspiration behind your business?

While seeking high-quality data to assist in the training of AI/ML products, we realized that we could not use production data, as it would breach data protection regulations, while the synthetic data available is generally generic and not contextually correct and therefore poor for training AI/ML models. As we further researched this area, we realized that most companies simply sit on their data but fail to utilise it, while some straight-up breach regulations and hope not to be discovered. This gave us the idea of creating a product that enables all companies to utilise their real data while protecting their customers’ personal information and meeting their regulatory obligations.

What is your magic sauce?

We were born out of the desire to enhance the development and use of Al/ML while respecting data privacy and protecting personal information. By creating tools that are developer friendly, we enable our technology to be used across all industries and applications. We also deliver our products in a manner that enables our customers to embed our technology within their own infrastructure and products without the need or risk of sharing their data with a third party. In short, we have created the “Privacy Layer for Software” in a form that can be used across all environments without PII being shared and which works across 45 different languages at exceptionally high accuracy.

What is the plan for the next 5 years? What do you want to achieve?

We are currently enhancing our product to support even more data formats and creating a user interface that will enable our customers to self-serve and self-administer the product. We are also expanding our sales and marketing resources and activities across North America and Europe, with the Asia-Pacific and Latin American regions to follow over the next two years. Our ultimate goal, which we expect to have achieved within the next five years, is to be recognized across all industry sectors and geographies as “The Privacy Layer for Software” and to set the bar as the technology and market leader in this sector.

What is the biggest challenge you’ve faced so far?

In the early days of the company, we focused initially on identifying Personal Information in images and videos, but based on market feedback, we quickly realized that the biggest demand was for the identification of PII within text, so we quickly refocused our efforts on addressing this opportunity.

The biggest challenge for us today is being “discovered”. Many companies don’t realize there’s such a solution available, or they attempt to build their own. But once we engage with a company, we are almost always successful in helping them address their challenges and unlock the true value of their data in a regulator compliant manner. So educating and evangelizing the market with thought leadership in this sector is a big part of getting known and building market demand.

How can people get involved?

We’d love to hear from anyone responsible for the use, analytics, security, development, and compliance of their company data, and of course, the development of Al/ML technology.

You can find out more about us at, where we offer lots of product, technical and use case information, access to our web demo, and a trial API key. Then contact us via, and we’ll be delighted to answer any questions and set up a trial or Proof of Concept for you.