Long-term, coherent conversations are the holy grail for enterprise AI agents. However, managing vast amounts of conversational history poses significant challenges related to context window limitations, computational costs, and data retention. This article dives into cutting-edge AI memory compression techniques that enable agents to maintain rich, extended dialogues without sacrificing performance or incurring prohibitive expenses. Discover how methods like summarization, embedding-based retrieval, and knowledge graphs are transforming enterprise AI capabilities.