Retrieval systems
Architectures for retrieval that stay fast, precise, and robust as similarity search becomes more dynamic and workload-aware.
KyroDB Research
Research for the memory layer of intelligent systems
We investigate the deepest bottlenecks in data infrastructure for retrieval, long-context systems, memory architectures, and the protocols required to make intelligent systems dependable at scale.
Focus Areas
Problems we care about for the next decade
Context infrastructure
Systems that make long-context applications practical by improving freshness, routing, compression, and reuse across requests.
Memory architectures
Persistent memory layers that learn from access patterns, preserve temporal coherence, and serve intelligent systems over time.
Protocols for intelligence
Interfaces and coordination primitives that let models, agents, and databases exchange state reliably at production scale.
Published Work