Agents lose context across tasks — shared long-term memory for multi-agent teams

Agents lose context across tasks — shared long-term memory for multi-agent teams targets a $36.0B = 3M dev/product teams x $12K ACV (team collaboration + AI developer tools spend) total addressable market with medium saturation and a year-over-year growth rate of 40%+ — rising demand for AI-first developer tooling and agent orchestration.

Key trends driving demand: Multi-agent orchestration -- growing experimentation with agent teams for complex workflows (research, automation, ops) increases need for coordination layers.; Vector databases and RAG -- embeddings + cheap vector stores make persistent semantic memory tractable and fast.; Shift to AI-native infra -- dev teams prefer modular stacks (LLMs + connectors + state) they can integrate and self-host.; Enterprise data governance -- companies want auditable, access-controlled agent context for compliance and safety..