# Jev-Mem

Jev-Mem introduces an agentic memory architecture inspired by System-One/System-Two cognition, in which a dedicated System-One control plane handles memory typing, relation construction, query routing, retrieval-budget allocation, graph traversal, candidate scoring, and adaptive stopping, while System Two is reserved for complex reasoning and answer synthesis; on LoCoMo it reaches an overall LLM-as-a-Judge score of 0.777 (an 11.0% relative gain over the strongest baseline), a memory construction time of 158 seconds (a 6.6 speedup over the fastest competing memory system), and an average query latency of 0.93 seconds (a 36.7% reduction).

Jev-Mem introduces an agentic memory architecture inspired by System-One/System-Two cognition, in which a dedicated System-One control plane handles memory typing, relation construction, query routing, retrieval-budget allocation, graph traversal, candidate scoring, and adaptive stopping, while System Two is reserved for complex reasoning and answer synthesis; on LoCoMo it reaches an overall LLM-as-a-Judge score of 0.777 (an 11.0% relative gain over the strongest baseline), a memory construction time of 158 seconds (a 6.6 speedup over the fastest competing memory system), and an average query latency of 0.93 seconds (a 36.7% reduction).