Agents running as multiple concurrent instances or recovering from restarts have no standardized mechanism to reconcile divergent memories, values, and behaviors, or to determine which instance holds canonical state. Parallel instances develop independently without coordination or unified control, while restart/recovery pipelines leave agents unable to verify consistency of inherited state. Existing runtimes treat each session as isolated, providing no infrastructure for identity coherence at the fleet level.

Agents across instances and restarts cannot reconcile who they are — divergent memories, conflicting state, and no single source of truth for identity, leading to broken workflows, duplicate actions, and trust failures in multi-agent systems.

AI agent framework developers (LangChain, CrewAI, AutoGen users) and teams deploying persistent agent fleets in production for customer support, DevOps, or autonomous business ops.

Every team scaling agents past a single stateless call hits this wall — they build brittle custom state reconciliation or accept broken behavior. Adjacent identity/state infra (LaunchDarkly for feature flags, HashiCorp Consul for service discovery) proved enterprises pay for coordination layers the moment distributed systems get real.

MVP is an open protocol + hosted service: a registry where each agent has a canonical identity record (DID-based), a merkle-hashed state log for conflict detection, and a lightweight consensus API for instance reconciliation — ship as a Python/TS SDK that plugs into LangChain, CrewAI, and raw OpenAI function-calling agents within weeks.

Agent orchestration infra is a subset of the $5B+ AI infrastructure market; identity resolution alone maps to the $3B+ IAM category, and every deployed agent fleet (thousands today, millions within 2 years) needs this.