The Research Hub
Advancing AI Long-Term Memory.
Memwyre Research Lab publishes studies, evaluations, and datasets exploring how entity graphs, pruning algorithms, and context compression solve statelessness in AI agent networks.
The LoCoMo Benchmark Report
Our core evaluation matrix checking long-context recall, entity traversal, and temporal consistency across 1,540 simulated developer query runs.
What is AI Memory?
A 3,000-word comprehensive technical analysis exploring cognitive memory structures, entity graphs, vector decay formulas, and workspace agents.
State of AI Memory 2026
An inspection of context window explosion and why stateless attention buffers create substantial financial and latency overheads for enterprise codebases.
Retrieval & Pruning Studies
Experimental results validating our mathematical decay functions: \(I(t) = I_0 \cdot e^{-\lambda t}\). Analyzing the correlation of memory reinforcement against query speed.
Advance Your AI Architecture
Access our open source benchmark repositories, integrate Model Context Protocol memory servers, and build stateful agents.