Reduce session context switching by centralizing long-term AI project memory

Reduce session context switching by centralizing long-term AI project memory targets a $4.2B = 1.4M target teams × $3K ACV (teams building AI-heavy products and knowledge workflows) total addressable market with medium saturation and a year-over-year growth rate of 35% YoY — developer AI tools and knowledge management adoption driven by LLM integrations (analyst composite of AI tooling and knowledge management markets).

Key trends driving demand: LLM adoption — As teams deploy multiple AI assistants, demand for a shared, persistent context store grows because models need relevant context to produce reliable outputs.; RAG mainstreaming — Retrieval-augmented generation is becoming best practice for accuracy and hallucination reduction, increasing demand for indexed project memory.; Vector DB commoditization — Managed vector databases and embedding APIs have lowered the engineering bar, enabling higher-level memory services to be built and adopted quickly..