Identify 50+ Entity Types in 33 Languages
Good NER Systems Are Hard to Find, Especially Self-Hosted Ones
Current Named Entity Recognition (NER) systems typically only work in English and support a handful of entity types. Such systems usually also aren’t focused on entities that matter for businesses, such as money amounts and mailing addresses.
Furthermore, most systems are limited to producing a single label per entity, rendering them unable to produce rich label structures.
Enter Private AI:
Realtime Entity Detection in 33 Languages
Private AI’s entity detection engine can be used for general-purpose NER. Find ZIP codes, addresses, drug mentions and more in over 30 languages. Each entity can have multiple tags, allowing for richer entity information.
Easily and cost efficiently support billions of inferences per month, all hosted in your own environment.
Why Private AI
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.
Major Cloud Provider 2
Open Source Software 2
Open Source Software 1
Major Cloud Provider 1
Major Cloud Provider 3
0.80 0.90 1
Try it yourself on your own data:
Private AI’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.