Don’t let your data get you in trouble: Detect and redact data with higher than human accuracy.
Building privacy into your workflows shouldn’t be hard. Private AI makes privacy and GDPR compliance fast, easy, and reliable.
No 3rd party processing required.
TEXT
Our contextual AI can quickly strip over 30 categories (and growing) of personally identifiable information from English, Spanish, French, Portuguese, Italian, German, and Korean (beta) text.
IMAGES
Easily remove faces, license plates, and sensitive text from stored images like IDs and crowd photos.
VIDEOS
Blur out faces, license plates, street names, and more from your video data.
Working with personal data?
ON PREMISE
IOT
WEB
APP
Our de-identification suite
We’ve 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). And with that comes a ton of benefits.
Unlock access to data sets with PII
Streamline software deployment
Reduce GDPR compliance overhead
Limit impact of data leaks
How our tech stacks up
Don’t believe us? We’re happy to go toe-to-toe in a performance test any day.
45ms Latency
We’re lightning fast on-prem, running over 25x faster than a reference NLP system on a single CPU core.
99%+ Accuracy
Our contextual NLP model delivers industry leading performance across more than 30 different types of PII, and we can easily add custom ones too.
32x Smaller
Private AI installs with just 3 lines of code into your on-prem, web, or mobile workflows, and tips the scales at just over 40MB.
Designed for developers
We’re easy to deploy in any workflow — on-prem, web, or mobile — with just a few lines of code, so you can quickly add privacy protection to your data pipeline and then get back to shooting the breeze with rubber ducks.
Use cases
Implementing Privacy by Design has typically been expensive and cumbersome. And even if personal data is encrypted, it becomes vulnerable any time it’s accessed, viewed, or processed by your team members. Using AI-powered de-identification solves both problems — freeing up datasets to be analyzed and mined for insights with a process that’s quick to implement and incredibly effective at protecting privacy. Here’s how it works for some of our partners:
Trusted By
We understand that using our technology to promise privacy to your clients means that you’re putting your reputation into our hands, and we take that responsibility incredibly seriously. But don’t take our word for it – here’s what our partners have to say about us and our technology:
“PrivateAI’s de-identification solution was extremely easy to integrate with our current pipeline, requiring only a few lines of code to ensure GDPR-compliant data handling for our users’ sensitive information. As a data anonymizer it was accurate and highly performant, allowing us to offer superior privacy protection without affecting our rates of service. Importantly, it enabled us to meet the rigorous data privacy requirements of the financial services sector without having to break the bank.”
— Damian Tran, CTO MinervaAI
“We provide a speech-to-text transcription API and needed to bring our redaction of credit cards, SSNs, and other personal financial and health information up to the highest accuracy level possible. Private AI made that quick and easy – now our accuracy numbers are through the roof and our clients are happy, which has been amazing. Plus they were remarkably easy to integrate into our existing workflows, which saved us a lot of time & effort compared to building something in-house, without our data ever having to leave our servers since we can run Private AI’s models on-premise.”
— Dylan Fox, CEO AssemblyAI
“The docker image was really easy to integrate into our data workflows and we had it up and running in just a few hours. Our data involves mental health chat transcripts, so we were very happy to see that we were hitting impressive accuracy numbers out-of-the-box on a wide range of entity types that matter to our customers, saving us an enormous amount of time compared to building it ourselves. Plus their team was great to work with.”
— Quinn Underwood, CEO Autumn AI