Manage Your Orders, Don
Monitor the entire process from order confirmations to proof of delivery (PoD) in real-time from a single platform. Prevent delays with proactive alerts, eliminate manual tracking, and take full control of your operations.
⚠️ Why Manual Order Tracking Falls Short?
Communication Overhead
Endless email traffic and calls; hundreds of contacts for supplier confirmations.
Lack of Visibility
Unclear
Delayed Actions
Reactive interventions; issues are noticed only after they affect operations.
💡 Quibas Farkı: Sizin yerinize çalışan, iletişim kuran ve sorun çözen otonom AI ajanları.
Autonomous Order Management with Agentic AI
Quibas Order Tracking is not just a dashboard. Our autonomous AI agents built on LangGraph proactively manage the full PO lifecycle — obtaining confirmations, detecting delays, sending reminders and notifying stakeholders in real-time.
Reduction in manual tracking effort
Reduction in order delays
Autonomous tracking and monitoring
Empower Your Order Processes with Smart Agents
Our Order Tracking product delivers end-to-end supplier communication, risk detection and ERP integration through autonomous agents.
Autonomous Supplier Communication
When a new order is created, our AI agent contacts the supplier to request confirmation; if there
Confirmation Automation
Supplier confirmations automated
Reminder Rules
Customizable reminder flows
Proactive Delay Detection & Alerts
The platform monitors confirmations, ASNs and PoDs in real-time. When an order is at risk of late delivery, AI agents alert both you and the supplier for early remediation.
Real-time Risk Monitoring
Order risks detected in real-time
Early Alerts
Alerts sent to supplier and stakeholders
Conversational AI Interface
No complex filters. Ask Quibas Order Assistant in natural language:
End-to-end Integration from PoD to Invoicing
The process doesn
Benefits You Will Gain
Operational Efficiency
Up to 95% reduction in manual tracking effort
Delay Reduction
Up to 50% reduction in delays
24/7 Monitoring
Continuous monitoring by autonomous agents