The problem AI is good at
Orders rarely arrive in a clean form. They come as emails, forwarded chats, PDFs, photos of a handwritten list. Retyping them is slow and error-prone. Reading unstructured text and pulling out the same fields every time is exactly what language models do well.
The flow that works
- The message or file lands in the CRM inbox.
- The model extracts client, items, quantities, addresses and dates.
- The system matches them to your client and product catalog.
- A draft order is created, with uncertain fields highlighted.
- A manager compares it with the original and confirms.
What does not work
Letting the model book orders on its own. Prices, quantities and addresses carry money; a confident wrong guess is worse than a slow correct entry. Keep a confirmation step, and keep the original next to the draft.
Practical points
- Match against your own catalog, not the model's guess.
- Log every extraction so mistakes can be traced and the prompt improved.
- Think about where customer data is sent and choose the provider accordingly.
- Start with one channel, for example email, then add the rest.
We built this as a layer on top of a CRM — see the AI order processing case, or ask us about your orders.