Context memory. Optimized.
EigenKV identifies redundancies in KV-cache to enable longer contexts with the same memory.
EigenKV
KV-cache is the main memory bottleneck in LLM inference. EigenKV detects and eliminates structural redundancies, enabling longer contexts or lower infrastructure costs.
1.7× Reduction
Significantly reduces KV-cache memory footprint.
<1% Loss
Minimal impact on generation quality, imperceptible in most cases.
Drop-in
Easy integration with existing inference pipelines.
See It Work
Real compression on real data. Try with our demo or upload your own embeddings.
Demo Note: This demo uses EigenDB vector compression technology. The results shown are specific to vector embedding compression. For KV-cache memory optimization, the principles are similar but applied to different data structures.
Click to analyze 1,000 random embeddings and see compression results
Use Cases
Long contexts in production
GPU cost reduction
Multi-tenant inference
Real Numbers
Validated on production data. No cherry-picking.
EigenKV Performance
EigenDB vs. The Competition
Real benchmarks on 384-dimensional embeddings (sentence-transformers)
| Metric | FAISSVerified | ChromaVerified | ElasticsearchVerified | WeaviateVerified | Pinecone | EigenDBVerified |
|---|---|---|---|---|---|---|
| Compression | 1x | 1x | 1x | 1x | 1x | 24xWinner |
| Recall@10 | 100% | 100% | 100% | 100% | 95%+ | 100% |
| Storage Cost | 100% | 100% | 100% | 100% | 100% | 4% |
| Search Latency | 1.39ms | 0.56ms | 5.86ms | 1.09ms | 26-60ms | 0.04ms |
| Index Build | 0.16ms | 40.5ms | 861ms | 1298ms | managed | 0.019ms |
Dataset: 500 embeddings, 384D (sentence-transformers/all-MiniLM-L12-v2). Benchmarks run on local hardware.
FAISS, Chroma, Elasticsearch, Weaviate: our benchmarks. Pinecone: official documentation data.
They don't compress. We do.
All competitors store 100% of dimensions. EigenDB compresses 24x while maintaining 100% recall. Less data = lower cost = same quality.
Fundamental Research
While our products solve immediate problems, our research aims further
Neural Ontology
Validated with real data: EEG, mouse neurons, human cognition
26/27 Tests Passed
Fundamental cognition principles verified experimentally
KAIROS Framework
Emergent intelligence from first principles
“We don't just build tools. We're redefining how intelligence emerges.”