Chatbots lose context — add semantic memory to retain past conversations

Chatbots lose context — add semantic memory to retain past conversations targets a $36.0B = 300M businesses x $120/year average spend on conversational memory features total addressable market with medium saturation and a year-over-year growth rate of 25%+ annual growth in conversational AI and vector-database adoption (enterprise).

Key trends driving demand: Embedding economics -- falling cost of generating and storing embeddings makes persistent memory affordable for even SMBs.; RAG standardization -- developer frameworks and providers have made retrieval-augmented workflows mainstream for production apps.; Customer expectations -- users expect contextual, continuous help across channels, increasing demand for memory-enabled bots.; Open-source vector DBs -- projects like Qdrant/Weaviate/Chroma lower infra costs and speed adoption of semantic memory..