AI Agent Long-Term Memory System

A shared memory database for AI agents (Claude, Codex, etc.) that teams can use to store, organize, and reuse institutional knowledge. Converts important memories into artifacts like style guides and design decisions to improve agent consistency.

The agent orchestration layer is actively being contested right now — LangChain, LlamaIndex, and mem0 are all pushing persistent memory as a core primitive, and enterprise teams running multi-agent workflows are hitting context loss as a real production problem, not a theoretical one. Mem0 is the closest incumbent, though it targets individual agent memory rather than team-level institutional knowledge as shareable artifacts. The $2k–10k/mo revenue band is plausible if sold to engineering teams on a per-seat or usage basis, since the value is directly tied to developer time saved on re-prompting and inconsistent outputs. The biggest risk is that foundation model providers — Anthropic, OpenAI — bake persistent memory natively into their APIs and eliminate the need for a third-party layer entirely, which is already partially happening with OpenAI's memory features.