Secure preparation of data for third parties
The module is primarily used as a secure data-preparation layer before information is sent to third parties, technology providers, cloud environments or internal areas with different levels of trust. Based on its preliminary dataset analysis, it determines which fields should be generalised, randomised or removed, and to what degree, according to their sensitivity and intended subsequent use. This enables information to be published, processed or shared for analytics, model training, research or service validation without directly exposing personal, financial, clinical or strategic data.
Privacy preserved without losing utility
The main benefit is the secure use of confidential data outside its original domain, reducing re-identification risk and supporting compliance with privacy requirements. By dynamically adapting anonymisation to each dataset, the solution avoids rigid approaches that unnecessarily degrade information. This preserves greater utility for analysis, statistical use, artificial intelligence or third-party collaboration. Field-level configuration also provides granular control, traceability of criteria and adaptability to different scenarios, sectors and levels of sensitivity.