The Quantstack Vector Engine
A private knowledge graph built for high-speed reasoning.
Core Memory Layer
Not a generic vector DB. The intelligence backbone of your LLM.
Sub-millisecond retrieval across millions of embeddings with quantum-inspired similarity scoring
Live indexing as your knowledge base evolves—no batch processing delays
Secure data partitioning with role-based access control built-in
Co-optimized with local models for maximum precision and zero latency
Documents, chat logs, images, structured data—unified in one semantic layer
Performance at Scale
Built for enterprise workloads with production-grade reliability
Average response time for semantic search across 10M+ vectors
Scalable to billions with distributed architecture
Enterprise-grade reliability with automatic failover
Support for all standard embedding models
Technical Architecture
Designed from the ground up for private deployment and enterprise security
Quantum-Inspired Similarity
Our proprietary scoring algorithm delivers 23% higher precision than cosine similarity alone, using concepts from quantum computing to better capture semantic relationships.
Hybrid Search Capabilities
Combine dense vector search with traditional keyword matching for optimal retrieval. Automatically tune relevance weights based on query patterns.
Incremental Updates
Add new documents without full re-indexing. Real-time embedding generation and index updates with zero downtime.
Deployment Options:
On-premises, private cloud (AWS/Azure/GCP), edge environments, or hybrid configurations. Full
data sovereignty guaranteed.
Seamless Integrations
Data Sources
- Document stores (S3, SharePoint, Drive)
- Databases (PostgreSQL, MongoDB)
- CRM/ERP systems (Salesforce, SAP)
- Communication (Slack, Teams, Email)
- Custom APIs and webhooks
Embedding Models
- OpenAI Ada-002, text-embedding-3
- Cohere Embed (multilingual)
- Custom fine-tuned embeddings
- Domain-specific sentence transformers
- Multimodal (CLIP, ImageBind)
Query Interfaces
- REST API with SDKs (Python, JS, Go)
- GraphQL endpoint
- Direct LLM integration
- Streaming responses
- Batch processing pipelines