Data Security

File-centric, protect-first approach

Intelligent De-
identification
Platform

De-identify sensitive data, including personally identifiable information (PII), through pseudonymization and anonymization for secondary use or analysis, such as comparative effectiveness studies, policy assessment and life sciences research. This is critical as organizations gather and compile large amounts of business data to understand trends, gain insights into customer preferences and develop new innovations. Regulations such as HIPAA and GDPR require that data be de-identified, but the challenge is that many de-identification tools focus on eliminating personal identifiers, but make it difficult to use the data. Transform PII into data that cannot be used to identify data while ensuring privacy using data anonymization and pseudonymization techniques. This allows you to effectively analyze large amounts of data without violating privacy regulations.

Intelligent De-identification Platform

De-identify sensitive data, including personally identifiable information (PII), through pseudonymization and anonymization for secondary use or analysis, such as comparative effectiveness studies, policy assessment and life sciences research. This is critical as organizations gather and compile large amounts of business data to understand trends, gain insights into customer preferences and develop new innovations. Regulations such as HIPAA and GDPR require that data be de-identified, but the challenge is that many de-identification tools focus on eliminating personal identifiers, but make it difficult to use the data. Transform PII into data that cannot be used to identify data while ensuring privacy using data anonymization and pseudonymization techniques. This allows you to effectively analyze large amounts of data without violating privacy regulations.

Unleash the value of big data without compromising security and privacy

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Safe and efficient data pseudonymization
and anonymization

De-identify data using selected methods and privacy models from broad areas of data de-identification and statistics to safely and efficiently utilize big data for secondary use and analysis of personal data.

De-identify data using selected methods and privacy models from broad areas of data de-identification and statistics to safely and efficiently utilize big data for secondary use and analysis of personal data.

Bridge the gap between privacy compliance
and business transformation

Analyze big data effectively and comply with regulations and standards such as HIPAA (Safe Harbor and Expert Determination methods), GDPR (data pseudonymization and anonymization), ISO 20889 and personal data de-identification guidelines.

Analyze big data effectively and comply with regulations and standards such as HIPAA (Safe Harbor and Expert Determination methods), GDPR (data pseudonymization and anonymization), ISO 20889 and personal data de-identification guidelines.

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Various privacy models to select from

Utilize various privacy models to best meet de-identification, analysis and privacy requirements such as k-anonymity, I-diversity, t-closeness, differential privacy, basic β-likeness, recursive-l, δ-presence.

Utilize various privacy models to best meet de -identification, analysis and privacy requirements such as k-anonymity, I-diversity, t-closeness, differential privacy, basic β-likeness, recursive-l, δ-presence.

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