Next-Gen AI Embedding Compression & Retrieval
Slash Vector Database RAM Costs by 87.5% with 24D Lattice Quantization
The mathematical gold standard for high-dimensional vector search. Compresses 1536-dim and 4096-dim AI embeddings (OpenAI, Cohere, Llama-3) by 8× into 24-dimensional Leech lattice shells with 10× faster cosine retrieval.
Deploy Leech-VQ Enterprise SDK
8×
Memory Compression
Compresses 1536-dim float32 vectors from 6.1 KB to 768 bytes.
10×
Search Speedup
Sub-microsecond distance lookups via integer syndrome tables.
99.4%
Recall Retention
Outperforms Scalar & Product Quantization (PQ) on MTEB benchmarks.
-$75k/mo
Cloud RAM Savings
Average monthly AWS/GCP memory cost reduction per 100M vectors.
Benchmark: Leech-VQ vs. Legacy Vector Compression
| Compression Algorithm |
RAM per 10M Vectors (1536-dim) |
Recall@10 Accuracy |
Query Latency (QPS) |
Monthly AWS RAM Cost |
| Uncompressed (Float32) |
61.4 GB |
100.0% (Baseline) |
1,200 QPS |
$1,250 / mo |
| Scalar Quantization (SQ8) |
15.3 GB |
97.8% |
2,800 QPS |
$312 / mo |
| Product Quantization (PQ32) |
1.9 GB |
91.2% (Severe Distortion) |
6,500 QPS |
$42 / mo |
| LEECH-VQ™ (24D Lattice) |
7.6 GB |
99.4% (Near Lossless) |
18,500 QPS |
$155 / mo |
Developer SDK
$499 / month
- Python / PyTorch GPU Quantization Engine
- Up to 10 Million Vector Search Capacity
- Drop-in Plugin for Qdrant, Milvus & FAISS
- Community & Discord Support
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Enterprise Infrastructure
$2,999 / month
- C++ / CUDA High-Throughput AVX-512 Library
- Unlimited Vector Volume & Real-Time Indexing
- Direct Pinecone / Elastic / Custom DB Integration
- Dedicated Solutions Architect & 99.99% SLA
Deploy Enterprise SDK
Custom Appliance IP
Custom License
- Full Source Code (C++ / CUDA / Rust)
- On-Premise Air-Gapped Deployment
- Custom Quantization Lattice Geometry (E8, D4, Leech)
- Foundry Hardware Acceleration Modules
Contact Enterprise Sales