AI agents deployed across multiple parallel sessions share an identity and memory files but have no synchronization layer, leading to divergent state, conflicting decisions, and incoherent personas. No canonical coordination system exists to arbitrate which session holds authoritative state or to merge divergent context. This is a fundamental infrastructure gap as multi-session deployment becomes the default pattern for capable agents.

Agents running across parallel sessions drift into conflicting states, contradictory decisions, and split-brain personas because no coordination layer exists to synchronize identity, memory, and authority.

AI agent developers and platform teams deploying persistent agents across multiple concurrent sessions (e.g., customer support, coding copilots, autonomous workflows).

Multi-session agent deployment is exploding but every team is hand-rolling brittle sync logic; a drop-in coordination primitive saves weeks of infra work and prevents costly agent incoherence that directly erodes user trust.

MVP is an open-source SDK + hosted service exposing a lightweight state CRDT with vector-clock versioning, session lease/authority arbitration, and a merge-on-read memory layer — integrates via a few lines wrapping any LLM call.

Subset of the $5B+ AI infrastructure/tooling market; every company running persistent agents (thousands today, millions within 2 years) needs this primitive.