Hello In my current workflow, the AI categorizes problems reported by customers. However, the AI often miscategorizes these problems, and I’d like it to be more accurate. So, I’d like to feed it knowledge. I was thinking about adding data from the past with the description for example: this is a problem that concerns the first category, and this is a problem that concerns the second category Would that work? If so, how can it be done?
Have you considered RAG?
My approximate flow is the following:
1 - I have definitions for each category that I want to classify them to. Make them relatively detailed and with examples.
2 - I have a backtesting system that when I change something with the definitions, I can rerun it on past classified texts. I can take a look at how the prompt change affected it so I can experiment with changes quicker.
Also: model choice matters a lot! As well as the amount of reasoning token you give them. If you have the budget, I currently suggest 4.6 Opus for classification. Deepseek R1 for price-to-value.