SecureVector

The Problem

 

For AI models to process data effectively, company documents must first be vectorized or transformed into a numerical format they can understand. The data points are then stored in three-dimensional vector databases.

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Since AI models only interact with the vectorized data, the employee access-level controls in the original document storage systems are no longer in effect. Until now, system administrators have manually resolved this by defining roles and assigning vector database permissions based on those generalized roles. This is known as role-based access control (RBAC) for vector databases. 

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The Solution

 

Unlike RBAC, SecureVector automates embedding the document permission protocols into the vectors. Thus, with SecureVector, enterprises can scale vectorization while maintaining their data integrity and internal access level architecture. This is a game-changer for the widespread use of AI on company internal data.

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AES-256, HTTPS, and end-to-end encryption. GDPR, SOC 1-3, ISO/IEC 27001, and ISO/IEC 42001 compliant. DPAs, SLAs, and audit rights. Support for CISO, legal, and risk committees.

 

The SecureVector APIs will launch in Q3 2025.

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