Cartly：基于Mnexium构建的iOS收据跟踪演示
刚刚发布了一篇关于Cartly的新案例研究，这是一款使用Mnexium驱动完整收据跟踪AI工作流程的iOS应用。我们非常想了解实现这样一个演示需要什么条件。
在这篇文章中，我们详细介绍了Cartly如何使用以下功能：
- 内存用于用户偏好和连续性
- 记录用于结构化收据和收据项的存储
- 单一的mnx运行时对象来控制身份、历史、回忆和记录同步
- 请求追踪数据包以便于审计和生产环境中的调试
演示流程涵盖了模式设置、收据图像捕捉、AI提取、记录持久化以及基于记录的聊天响应。
博客链接：<https://mnexium.com/blogs/introducing-cartly>
文档链接：<https://mnexium.com/docs>
iOS代码链接：<https://github.com/mnexium/cartly>
查看原文
Just published a new case study on Cartly, an iOS app that uses Mnexium to power a full receipt-tracking AI workflow. We really wanted to see what it would take to get a demo like this up and running.<p>In the post, we walk through how Cartly uses:<p>Memory for user preferences and continuity<p>Records for structured receipts and receipt_items storage<p>A single mnx runtime object to control identity, history, recall, and record sync<p>Request trace packets for auditability and debugging in production<p>The demo flow covers schema setup, receipt image capture, AI extraction, record persistence, and record-aware chat responses.<p>Blog: <https://mnexium.com/blogs/introducing-cartly><p>Docs: <https://mnexium.com/docs><p>iOS code: <https://github.com/mnexium/cartly>