Today, I’m excited to share our latest research on “Building production ready AI Agents with Scalable Long-Term Memory”. We’ve achieved state-of-the-art (SOTA) performance—26% more accurate than OpenAI Memory. We evaluated Mem0 on the LOCOMO benchmark and found that it consistently outperformed all the six baselines on all types of questions from multi-hop to temporal. Mem0 reduces latency by 91% and cuts token usage by over 90% compared to full-context methods, offering fast and cost-effective performance. Today’s AI agents quickly forget important information once it moves beyond their context window, leading to broken conversations, repeated mistakes, and lost user trust. Larger context windows only delay the issue - making systems slower, more expensive, and harder to scale. Mem0 was built to solve this head on - giving AI Agents a scalable memory layer that remembers what matters, reasons faster and adapts over time. Check out the full paper below 👇🏻