We recently built a full AI-driven booking and customer management system using Acklix. A structured system that handled: Flight bookings Cancellations and modifications Real-time status updates Customer support queries Controlled multi-channel responses (WhatsApp and email) Access restrictions and workflow rules The interesting part was orchestration. The system could: Track booking state Execute real actions (cancel, reschedule, update records) Maintain consistent logic across channels Restrict responses to verified users Be toggled, scoped, or scheduled Technically, it worked. When we pitched it to a company, the response wasn’t about performance, safety, or architecture. It was about market maturity: Which raises an interesting question for this community: How do we evaluate AI systems for production readiness? AI systems are increasingly moving from “generate text” to “execute workflows.” But once AI starts booking flights, modifying reservations, or handling customer state, the evaluation criteria shift dramatically. So I’m curious: For those working on AI in production What signals make you trust a system enough to let it operate on real business workflows? submitted by /u/Sad_Impact9312
Originally posted by u/Sad_Impact9312 on r/ArtificialInteligence
You must log in or # to comment.