VectaX

Protecting The Core Of Generative AI

Industry First Security Layer For

Vector Databases & Large Language Models

Industry First Security Layer For

Vector Databases & Large Language Models

Secure Vector Database

Enhanced Vector Security

Enterprise-grade security for vector operations with similarity-preserving encryption. Protect your embeddings while maintaining searchability.

Encrypted Semantic Search

Enables the indexing and retrieval of data while it remains fully encrypted. Enable queries on sensitive data without exposing it, maintaining privacy and security without sacrificing the functionality of search systems.

Format-Preserving Encryption

Encrypt sensitive data while maintaining format and searchability. Perfect for securing metadata, PII, and structured data.

Vector Database Interoperability

Compatible with all leading vector databases, ensuring consistent security enhancements.

Role-Based Access Control

Incorporate role-based access controls directly into your vector embeddings multi-dimensional policies.

Control access at role, group, and department levels with comprehensive audit trails.

Privacy Preserving AI

Protect every phase of your machine learning and RAG workflows, ensuring data integrity and confidentiality from data ingestion through processing.

Vector Database Agnostic

Secure RAG with VectaX

Benchmark Performance with Encryption

P95 and P99 Latency (ms)

These represent the time it takes to complete a search query. P95 means that 95% of queries are completed within that time, and P99 means that 99% of queries are completed within that time. Lower numbers are better, indicating faster search times.

RPS (Requests Per Second)

This indicates how many search requests the engine can handle per second. Higher numbers are better.

Base Precision → Encrypted Precision

This shows the drop in accuracy due to encryption. For example, Qdrant's precision decreased from 0.99 to 0.95 with encryption.

P99 + Enc (ms)

The P99 latency including the encryption overhead.

Key Takeaway: Minimal Impact on Latency

As the data indicates, VectaX's encryption has a minimal impact on latency; for example, the P99 latency remains the same for Qdrant, Weaviate, and Elasticsearch after encryption5. Also, the precision only drops by a consistent 0.04 across engines. This demonstrates the efficiency of VectaX encryption.

Security Layer for LLM

LLM Model Protection

Strengthen defenses against model theft with robust security protocols, ensuring edge based LLM remains exclusive and secure from unauthorized replication or access.

Privacy Preserving Inferences: Ensuring Integrity

Encrypted inferencing ensures the integrity and confidentiality of data, from input through to output, maintaining its accuracy and preventing tampering or unauthorized disclosure.

Role Based Access Control

Integrate role-based access control in LLMs to secure and regulate user interactions, ensuring compliance and data protection.

Secure LLM Finetuning

Enhance Large Language Models with finetuning that utilizes encrypted data,

ensuring data privacy and compliance while preserving the integrity of the training process.

Let's Talk how we can encrypt your AI artifacts!

We’re excited to connect with you! Our founders are available for personalized meetings to discuss Mirror Security, AI protection strategies, and how we can help your business.

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