Protect Sensitive Patient Information and Safely Pull Insights to Deliver Enhanced Care
The Problem:
Identifying (and Removing) Sensitive Information from Healthcare Datasets
There arguably isn’t any messier data on the planet than a doctor’s handwriting in a scanned PDF. But for our customers in the healthcare sectors, there’s a stunning amount of value in those datasets.
So how do data science teams access those EHRs in a way that’s HIPAA-compliant and satisfies expert determination de-identification requirements?
Enter Private AI:
Accurately Protect Patient Data
Private AI uses contextual understanding to identify PHI within Electronic Health Records (EHRs), clinician’s notes, and transcripts of physician conversations with incredibly high accuracy.
The output is HIPAA-compliant data that ML and data science teams can safely utilize.
Patient privacy is paramount
Our solution is delivered via a container that you deploy in your own infrastructure (public/private cloud, on-prem) so the data never leaves your environment and is never shared with an external third party (including Private AI).
Why Private AI
- Process 70,000 words per second
- Can deliver real-time redaction
- No third party access
- Comply with privacy regulations like HIPAA, GDPR, CPRA, and more
Unrivalled Accuracy
Private AI uses the latest advancements in machine learning to achieve remarkable accuracy out of the box. See how we stack up against our competitors in our technical whitepaper.
Private AI
Major Cloud Provider 2
Open Source Software 2
Open Source Software 1
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Try it yourself on your own data:
Private AI scored best on our hybrid patient/provider PII test sets, and offers advanced features that we can customize to our needs. We quickly got state-of-the-art performance on challenging de-identification tasks critical to our business, at a fraction of the cost of doing it in-house.
François Huet
Head of Engineering, Curai Health