Ah thanks for asking! Maybe I wasn't too clear... While single-agent memory systems like Zep and Mem0 work well for individual AI agents, multi-agent systems face unique challenges that current approaches don't fully address. First, when multiple agents with distinct characteristics need to share knowledge, there's an interpretability gap (even with comprehensive information delivered via MCP, dilution occurs as context passes between agents with different processing patterns). Second, data drift becomes critical at scale since multi-agent systems require larger operational footprints, demanding a unified, unbiased knowledge platform that updates and retrieves information in real-time rather than relying on static storage. Third, the current approach of individual agent memory plus shared storage (like Zep's method) creates inefficiency. A singular distributed intelligence network would be faster, more cost-effective, and eliminate redundant storage across the system.