I built a business-memory AI that watches your shop's database and tells you what's wrong
I run a retail shop. Every morning I used to open the POS reports and dig through yesterday's numbers to find out what went wrong. Most mornings, nothing had. Some mornings, something had β a supplier going quiet, a till
I run a retail shop. Every morning I used to open the POS reports and dig through yesterday's numbers to find out what went wrong. Most mornings, nothing had. Some mornings, something had β a supplier going quiet, a till that stopped ringing, one item suddenly selling 10x β and I'd only find it days later, after it had already cost me money.
So I built Cuedis: a business-memory AI that watches your shop's database and tells you what's wrong, in plain words, before you go looking for it.
What it does
Cuedis sits beside your POS, ERP or accounting database (SQL Server / MySQL). It's read-only β it never writes to your data, and it runs on the shop's own PC, so the data never leaves the store.
It learns what's normal for your business, then every morning it sends a short briefing on Telegram:
- What's changed since yesterday β a big void, a till gone quiet, an item selling 10x
- What it's worried about, ranked by evidence
- The story so far: what's been going on over the last days and weeks
And you can just ask it questions in plain words β "which supplier has been late most this month?" β and get an answer in about a second.
Why I built it this way
On my own store it matched the POS reports to the cent. The thing I cared about most was that it had to work for a shop owner, not a data analyst: no dashboards to learn, no queries to write. A short message on your phone each morning, and an alert the same day something changes.
Try it
It's free for one database β register and download the free version at https://cuedis.com
It's also live on Product Hunt today: https://www.producthunt.com/products/cuedis
Honest feedback welcome β especially from anyone running a shop on a local SQL database. What would you want it to watch for first?
Originally published by Dev.to AI. Aggregated on AIWithGhost for educational purposes β full credit and traffic to the original publisher.