in

Private AI Delivers Companies an Easy-to-Deploy Way to Redact Sensitive Data on the Files They Share

Private AI has created a range of cutting-edge AI models that quickly and cost-effectively redact large datasets (text, image, video, audio) to provide privacy without the use of 3rd party cloud providers or new infrastructure. All it takes is 3 lines of code integrated into your existing workflows (on-premise, mobile, web, you name it). Our mission is to make privacy accessible to developers.

What problem are you trying to solve? 

Back in 2019, we noticed that it was very difficult for developers to integrate privacy into their software pipelines. We wanted to bring some awesome NLP tech to market, but it required a layer of privacy that simply did not exist in the market. That’s when we decided to commercialize that layer, so that companies wouldn’t have to take their teams’ attention away from their core product to work on privacy solutions. Ultimately, the developer/data scientist/machine learning engineer is the one integrating our solution, so everything we build is obsessing over the developer experience.

How are you solving that problem?

We make it really easy for companies to detect personal data within semi-structured and unstructured data and redact, pseudonymize, or de-identify that data, particularly focusing on text or text within images.

How has the pandemic impacted your company?

Initially, several of the customers we had lined up in 2019 ended up delaying engaging with us for several months as the world got used to covid 19. We were a remote team from the start, with one co-founder in Berlin and two in Toronto, but what did change was the need for an office space in Toronto (which saved us money) and the willingness of potential customers to speak over video call or otherwise connect online. The extra time I had to spend taking care of my toddler due to daycare being shut was made up by having to spend no time commuting or traveling.

Where do you see your company going in 5 years?

We are aiming to be the Twilio of privacy: taking a huge amount of complexity and making it accessible in only a few lines of code. 

What is the next big challenge in information security?

One major problem the GDPR and other data protection regulations have brought to light is just how much data companies have that they are not even able to catalogue. The major challenge we see companies continuously having is the inability to properly identify the personal data across all of their databases and the difficulty in highly accurately classifying personal data. There’s also generally still a lot of stress around how to reconcile the different regulations across various jurisdictions, which is only getting worse as more pop up. 

How do people get involved/buy into your vision?

We love speaking to data scientists, machine learning engineers, developers, and their managers to hear about the data privacy questions they have and see if we can help with their challenges, either through the use of our tech or pointing them to a suitable solution to their problems.

Comments

Leave a Reply

Your email address will not be published.

Loading…

0

NeuVector Provides Simplified Container Security and Data Protection to Security, DevOps, and Infrastructure Teams

DigitalTrack Solutions Its a Client-First Tech Vendor Providing Client with High-Quality Techonological Infraestructure