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Setting up an MLOps platform & pipeline in the cloud to continuous deliver Machine Learning Models.
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Classification
Warn when sensitive information, such as passwords, is shared.
Administrators of the knowledge management system.
A smart system that detects sensitive information, making the knowledge management system more secure.
Companies are increasingly collaborating to launch new products, services, or innovations. For this, employees of different companies must be able to share information confidentially. Because it sometimes concerns competition or stock market-sensitive information, confidentiality is very high.
We created a platform where corporate requirements such as onboarding, and other compliance requirements are guaranteed to keep this safe and efficient. This platform is used by international central banks, among others.
Because large groups of employees from different companies work together and use the collaboration platform, authorization and control are essential. Although good agreements are in place, users can still accidentally share sensitive information. Because the system has many users who add or change information daily, it becomes increasingly challenging to detect sensitive information.
All user additions and changes route through a funnel of machine learning models, which checks the data for sensitivities. First, there’s a coarse search for sensitive words, such as passwords, then words are examined in the context of the sentence, and at the bottom of the funnel, a classification is made based on allowed patterns. A phone number can look like a password, but of course, it isn’t.
The system reports the outcome to the administrators of the system. They will receive a notification containing a reference to the document where sensitive information is shared. The administrators make the final judgment about the sensitivity of the data.
The platform is gradually improving without any inconvenience to users. Controlling sensitive information is getting smarter and alerting administrators so they can act. It makes sharing information more secure.
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Setting up an MLOps platform & pipeline in the cloud to continuous deliver Machine Learning Models.
Get a proof-of-value of a Machine Learning Model within 5 days with our standard approach.