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.
In the post, we walk through how Cartly uses:
Memory for user preferences and continuity
Records for structured receipts and receipt_items storage
A single mnx runtime object to control identity, history, recall, and record sync
Request trace packets for auditability and debugging in production
The demo flow covers schema setup, receipt image capture, AI extraction, record persistence, and record-aware chat responses.
In the post, we walk through how Cartly uses:
Memory for user preferences and continuity
Records for structured receipts and receipt_items storage
A single mnx runtime object to control identity, history, recall, and record sync
Request trace packets for auditability and debugging in production
The demo flow covers schema setup, receipt image capture, AI extraction, record persistence, and record-aware chat responses.
Blog: <https://mnexium.com/blogs/introducing-cartly>
Docs: <https://mnexium.com/docs>
iOS code: <https://github.com/mnexium/cartly>