CatOrder: WhatsApp orders to draft orders

Wholesale distributors still take orders the way their customers talk: a WhatsApp message at 6 a.m., a voice note from the van, a photo of a handwritten list. Someone at the order desk retypes each one, guessing what "the usual" means and whether the price is the one agreed. CatOrder does the reading. Gemma 4 31B, served on AMD Instinct GPUs through AMD Token Factory, extracts every line from text, voice-note transcripts and photos, matches it to the catalogue, and resolves "the usual" or "same as last week" from the customer's order history. Each line is checked against the customer's agreed terms, so a wrong price, an odd quantity or an ambiguous product gets flagged instead of slipping through. The order desk gets a draft order where every line points back to the exact words it came from. A person confirms; nothing is sent on its own. When something is unclear, the model drafts a WhatsApp reply for the operator to edit and send. Real messages arrive live through the Twilio WhatsApp sandbox. On 20 synthetic messages (WhatsApp, photo, voice, email), Gemma 4 31B on Token Factory got 70 of 70 lines and 20 of 20 orders right, and found all 8 expected flags with one false flag. The whole run took 84k input and 6.6k output tokens, about 21 seconds per message. Built in TypeScript with Hono and SQLite, with a plain frontend and no framework. All data is synthetic. MIT licensed.