Sulcus reimagines AI memory as an active OS-like system with thermodynamic decay, where memories have relevance scores a
Sulcus moves AI memory from a passive database (search only) to an active operating system (automated management).
The Core Shift Current memory (Vector DBs) is static. Sulcus treats memory like a Virtual Memory Management Unit (VMMU) for LLMs, using "thermodynamic" properties to automate what the agent remembers or forgets.
Key Features Reactive Triggers: Instead of the agent manually searching, the memory system "talks back" based on rules (e.g., auto-pinning preferences, notifying the agent when a memory is about to "decay").
Thermodynamic Decay: Memories have "heat" (relevance) and "half-lives." Frequent recall reinforces them; neglect leads to deletion or archival.
Token Efficiency: Claims a 90% reduction in token burn by using intelligent paging—only feeding the LLM what is currently "hot."
The Tech: Built in Rust with PostgreSQL; runs as an MCP (Model Context Protocol) sidecar.