Original Summary

Every agent I shipped during my first year greeted returning users as strangers and I used to solve it by pasting the whole history back into the prompt which grew expensive month by month. to solve that once and for all, I built Synap, memory the layer to settle that properly and it runs live at https://maximem.ai/synap . It keeps whatever your agent learns so a customer who returns three weeks later arrives already known. What it handles on your behalf: Typed facts drawn out of each conversation as it happens, in place of raw transcripts. Automatic identity matching, so Murthy, Murthy Gupta and MG resolve to a single person. Replacement of stale facts the moment fresher ones arrive. Retrieval close to fifteen milliseconds, quick enough for voice agents. * Native support across twenty two frameworks, LangChain, LangGraph, CrewAI and the Claude Agent SDK among them. on a standardised LongMemEval run it reaches 92%, while Mem0 reaches 57.5 and Supermemory 71.3 under the same configuration. The free tier is live with 5000 credits behind a Google or GitHub sign in. Tell me how you hold state between sessions today and I will say honestly whether this improves on it.   submitted by   /u/mahalakshmivulavala [link]   [comments]

  • 情报分类：商业与市场研究
  • 分类依据：内容涉及商业、投资或市场动态
  • 信息来源：Reddit · SaaS
  • 发布时间：2026/9/30 02:07:34