Control AI memory to prevent context pollution in developer workflows

Control AI memory to prevent context pollution in developer workflows targets a $6.0B = 2M businesses × $3K ACV total addressable market with medium saturation and a year-over-year growth rate of 25% YoY (Source: synthesis of analyst reports on AI developer tools and RAG adoption, 2024-2026).

Key trends driving demand: Widespread RAG adoption — as more apps use retrieval to augment LLMs, the need to manage what is stored and how it is retrieved becomes essential.; Enterprise AI governance demands — compliance and auditability requirements push companies to prefer managed memory policies over ad-hoc storage.; Model-agnostic middleware gains traction — teams want solutions that work across OpenAI, Anthropic, Gemeni and open models to avoid vendor lock-in.; Context window expansion — larger context windows make it attractive to persist more data, increasing the risk of context pollution without controls..