LLM forgetfulness — structured multi-layer memory for Claude-like models

LLM forgetfulness — structured multi-layer memory for Claude-like models targets a $40.0B = 500,000 software orgs x $80K ACV (enterprise AI infra & tooling across industries) total addressable market with medium saturation and a year-over-year growth rate of 45% — rapid growth in AI tooling and enterprise LLM adoption.

Key trends driving demand: LLM adoption -- more production AI agents increases need for persistent, consistent context across sessions and channels.; Retrieval & embeddings -- improved embeddings and vector DB performance make low-latency memory retrieval practical.; Enterprise AI governance -- demand for provenance, retention policies, and audit trails raises value of structured memory layers.; Multi-modal assistants -- rising use of agents spanning chat, email, docs increases the amount of state to persist..