LLM sessions lose context — persistent per-user memory stored externally

LLM sessions lose context — persistent per-user memory stored externally targets a $12.0B = 20M developers x $600 ARPU (annual) for AI-first developer tooling and productivity add-ons total addressable market with medium saturation and a year-over-year growth rate of 30-45% annual growth (AI developer tools and RAG adoption).

Key trends driving demand: RAG commoditization -- standard patterns and libraries (LangChain, LlamaIndex) make memory integration straightforward for apps; Vector DB maturity -- hosted vector databases (Pinecone, Weaviate, Supabase vector) reduce infra friction and cost; Agent & workflow automation -- agents need persistent context to be truly useful across multi-step tasks; Privacy & data ownership -- demand for customer-controlled keys and audit trails is rising, favoring enterprise-friendly memory solutions.