- B2B
- Early StageStartup in initial stages
Private AI careers
Private AI provides a suite of ML models that are hyper-accurate at detecting PII in unstructured data (99.5%+), can pick up more than 50 different entity types, and operate in 42 languages (and counting).
We package our models into a Docker container and allow our customer's to run our models directly within their own environment (on-prem, private/public cloud, etc.) on CPUs or GPUs, so there's no new infrastructure or sending data to a 3rd party via API calls. Instead, all our customers' data never leaves their own workflows, and that data is never shared with us. Ever.
Our models can also generic synthetic data, which replaces PII with 'fake entities' that make it indistinguishable from the original data. This is perfect for ML model training: synthetic data is fully de-identified and safe for sharing, and won't affect model performance with clunky entity tokens or black boxes.
The result is data that's safe for sharing, protects user privacy, and makes our customers compliant with global privacy leglisation.
We package our models into a Docker container and allow our customer's to run our models directly within their own environment (on-prem, private/public cloud, etc.) on CPUs or GPUs, so there's no new infrastructure or sending data to a 3rd party via API calls. Instead, all our customers' data never leaves their own workflows, and that data is never shared with us. Ever.
Our models can also generic synthetic data, which replaces PII with 'fake entities' that make it indistinguishable from the original data. This is perfect for ML model training: synthetic data is fully de-identified and safe for sharing, and won't affect model performance with clunky entity tokens or black boxes.
The result is data that's safe for sharing, protects user privacy, and makes our customers compliant with global privacy leglisation.
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Patricia Thaine
John Stocks
Valuation
$0
Funded over
1 round
Latest round
Series A (Nov 2022)
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