Secured AI

Secured AI is a privacy-first AI assistant for protecting sensitive data across AI workflows.It automatically detects common sensitive elements—names, emails, phone numbers, organization names, account numbers and identifiers—and supports custom patterns.

Detected values are replaced with system-generated placeholders that preserve structure and context so models can operate without raw data exposure.A zero-knowledge vault encrypts sensitive values locally with a client-controlled master key; de-obfuscation and restoration of original values occur on-device.

Compatible with major model endpoints (OpenAI, Grok, Claude; additional models planned) and designed for regulated environments.Target users include healthcare, financial services, legal teams and enterprise security/compliance groups seeking PII/PHI protection during AI use.

Key benefits.on-device encryption, context-preserving obfuscation, customizable detection patterns, and workflow-level data protection that preserves AI usability.

Key Features

• Automatic detection of common sensitive data (names, emails, phone numbers, organization names, account numbers, identifiers)
• Support for custom detection patterns
• Context-preserving system-generated placeholder obfuscation that preserves structure and context
• Local zero-knowledge vault with client-controlled master key and on-device encryption/decryption
• Integration with major model endpoints (OpenAI, Grok, Claude)

Use Cases

• Process customer support transcripts with SecuredAI to automatically detect and obfuscate PII/PHI (names, emails, phones, orgs, account numbers and custom patterns) before sending data to analytics or LLMs, preserving conversational context with placeholders while storing originals encrypted in a zero-knowledge on-device vault for secure restoration
• Integrate SecuredAI into telehealth and clinical documentation workflows to mask PHI (patient names, MRNs, contact details and clinical identifiers) with context-preserving placeholders for compliant AI-assisted review and collaboration, while keeping originals locally encrypted to meet HIPAA and audit requirements
• Train and validate internal ML models and share de-identified datasets using SecuredAI's custom pattern detection and PII masking to retain contextual signals for model quality, enabling safe model development and compliant data sharing with originals secured in a zero-knowledge vault on-device

Who is it for?

• Ml engineers
• Data scientists
• Privacy officers
• Enterprise security teams
• Compliance teams