Context memory for inference.
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
Low impact on generation quality in our tests.
Drop-in
Easy integration with existing inference pipelines.
Technical demo
Try compression on demo embeddings or upload your own file.
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
Measured results
Internal benchmarks with documented methodology.
EigenKV Performance
EigenDB compared with alternatives
Benchmarks on 384-dimensional embeddings (sentence-transformers)
| Metric | FAISSVerified | ChromaVerified | ElasticsearchVerified | WeaviateVerified | Pinecone | EigenDBVerified |
|---|---|---|---|---|---|---|
| Compression | 1x | 1x | 1x | 1x | 1x | 24xBest result |
| 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.
The main difference is compression.
In this benchmark, alternatives store all dimensions. EigenDB reduces dimensions and preserves measured recall.
Core Research
Alongside products, we maintain theoretical and experimental work on intelligent systems.
Neural Ontology
Evaluated with EEG, mouse-neuron, and cognitive-task data.
Experimental batteries
Results recorded in internal and external tests where appropriate.
KAIROS Framework
Conceptual framework for organizing hypotheses about intelligent systems.
“We combine practical tools with documented theoretical research.”