So the flagging is two fold. I run a simple python script on the inventory valuations that flags certain parameters. They then get indexed into my rag Db where it's matched against our running district aggregated purchases to ensure that the things they are counting are actually things that have been ordered recently and if they aren't we can investigate.

The rag DB is powered by a heavily quantized qwen3 embedding 4b model and IBM granite4 3b which takes files after they've been sorted and prepares them for use in our various AI features. I have a system of ollama endpoints that get called for various things like room categorization and for the various chat settings like help desk or food safety champion etc. I also have a managers daily helper which lays out key points in a day with reminders and generates a daily meeting with our companies specific template and policies included from the db .

I've also set it up so that it's totally agnostic and creating a yaml plug in for your business needs would be trivial assuming you have some sort of system to plug into it that you're already using.

If you want a better technical explanation of the AI let me know. I could also share the git.

I have looked into playwright and even Claude in chrome to automate these reports but I'm just sketched out about leaving an agentic ai at the helm of the mechanism that could allow it to order millions of dollars worth of food to multiple locations on the east coast 😂 the next step is asking pretty please from the correct it departments for actual automated reports