Original Summary

I built SupportMemory AI , an AI customer-support agent designed to remember useful information from previous customer interactions instead of treating every conversation as completely new. What it does The system maintains a persistent memory layer for each customer and can recall: Previous support issues Customer environment and setup Solutions that worked previously Solutions that didn't work Recurring problems Useful customer preferences and facts The memory layer is powered by Hindsight . Example In the demo, Sarah Johnson previously contacted support about a CloudDesk login problem while using Windows 11 and Chrome. A previous troubleshooting attempt found that clearing her session/cookies resolved the issue. When Sarah encounters a similar login problem later, SupportMemory AI can retrieve that previous information and use it when generating the new response instead of starting the troubleshooting process from scratch. I also included a Memory ON/OFF mode so the difference between a normal support interaction and a memory-aware interaction can be demonstrated directly. How it works Customer message → Customer identification → Memory recall → Personalized AI context → AI response → Durable-fact extraction → Memory retention → Updated customer memory Tech stack Frontend: Next.js 14, React, TypeScript, Tailwind CSS, Lucide Backend: Next.js Route Handlers Memory: Hindsight AI: OpenAI-compatible API with a rule-based fallback One of the harder parts was deciding what information should become long-term memory rather than simply storing the entire conversation history . I'm sharing this as a project I built and would be interested in technical feedback, particularly around long-term memory design for AI agents.   submitted by   /u/bhavitha07_ [link]   [comments]

  • 情报分类：技术学习与提效
  • 分类依据：内容涉及技术、AI、软件工具或工程实践
  • 信息来源：Reddit · SideProject
  • 发布时间：2026/9/29 22:45:33