Safeguard Unstructured Data for AI
Up to 90% of organizational data is now unstructured, residing in documents, emails, presentations, and multimedia files, leading to ethical and sometimes legal issues when used to train or support AI systems. For example, digital documents like medical, insurance, and tax forms often contain sensitive and personal data, raising concerns about privacy regulations like GDPR, HIPAA, and CCPA.
Ensuring your unstructured data complies with privacy regulations can be a complex challenge. Traditional data security measures struggle to handle the complexities of these diverse data formats, leaving organizations vulnerable to data breaches, regulatory fines, and reputational damage.
Cypher safeguards sensitive and personal data in unstructured data for responsible AI compliance.
Detect
Scan unstructured files for sensitive and personal data
Protect
Anonymize sensitive and personal data from detected files
Report
Inventory of total files scanned and number of elements anonymized
Diversified AI Data
Optimize unstructured data for AI training
- Safely integrate unstructured data from on-premise, cloud, and SaaS platforms
- Source data from any existing file and object storage to gather comprehensive datasets for AI training and other analytical purposes
Compliant AI Privacy Preservation
Sanitize unstructured data for legal and ethical compliance
- Transform data into a privacy-preserving format to comply with data privacy regulations
- Dynamically mask PII and sensitive data from unstructured data to secure privacy protection
Unstructured AI Data Governance
Simulated red teaming automates expert attacks with zero lead time
- Stress-test your AI defences through dynamic, scenario-based simulations (tabletop exercises).
- Quantitatively assess the effectiveness of various known defences against adversarial attacks.
- Strategically allocate resources to strengthen your AI security posture