Data Management

Conversational AI has brought about a major breakthrough in how we handle data. AI-ris is ready to help its clients take full advantage of this technological revolution.

 

Data Anonymization

Data anonymization is an essential technique to protect user privacy when handling sensitive data. It involves replacing, masking, or removing personal information in datasets, making it nearly impossible to identify individual users. At AI-ris, we employ robust and advanced anonymization techniques to safeguard customer privacy.

 

Anonymization not only provides compliance with regulations such as GDPR, but also contributes to building trust with customers. Our large language model-based anonymization tool uses various techniques that both guarantee privacy and maintain the usability of the data for analysis and machine learning.

 

Synthetic Data Creation

While anonymization focuses on protecting the identities of individuals in existing datasets, synthetic data generation goes a step further. It's an innovative technique where artificial datasets are generated that retain the characteristics of the original dataset but have no direct link to the original data.

 

At AI-ris, we use advanced algorithms, including Generative Adversarial Networks (GANs), to generate realistic synthetic datasets. These datasets can be used for testing models, training algorithms, and performing analyses without any risk of privacy violation.

 

Moreover, the creation of synthetic data makes it possible to generate data for scenarios that would be difficult to obtain in reality, allowing companies to test their models against exceptional or extreme situations.