Prevent AI 'forgetting' by adding persistent, searchable model memory

Prevent AI 'forgetting' by adding persistent, searchable model memory targets a $30.0B = 250,000 enterprises x $120K ACV (enterprise AI memory & MLOps spend) total addressable market with medium saturation and a year-over-year growth rate of 30-45% (enterprise AI tools & MLOps growth, vector DB adoption accelerating).

Key trends driving demand: Retrieval-augmented generation mainstreaming -- Drives demand for reliable, versioned context stores to improve accuracy of LLM outputs.; Vector DB commoditization -- Lower infrastructure friction makes packaged memory services viable and expected by dev teams.; Enterprise AI adoption -- More customer-facing AI increases cost of model inconsistency and drives requirements for auditable memory.; Tooling integration -- Open-source toolkits (LangChain, LlamaIndex) create standard integration points for managed memory services..