AI-Powered Customer Appointment Management
What we deliver
The Problem (Before)
Companies that deliver to retailers or large customers must create and update appointments in the customer's scheduling system. This is entirely manual today: logging into customer portals, entering data, updating on changes. High volume, high error rate.
Transportation Manager, Customer Compliance Analyst
The Outcome (After)
Appointments in your customer's systems set and updated automatically by AI. No portal logins, no manual entry.
Shippers manually log into each retailer's appointment portal to create and update appointments. This AI agent handles the portal interaction autonomously, eliminating hours of manual data entry across customer systems.
Alan
How it works
An AI agent logs into your customers' appointment portals on behalf of the shipper, creates and updates appointments based on ETAs, and captures confirmation numbers automatically.
Carrier delivery reliability for appointment accuracy
Customer-specific appointment window patterns
Historical appointment compliance rates
This intelligence exists because the Graph aggregates behavior across 882 enterprise shippers, 10,164 carriers, and 3.6 million facilities over 11 years.
Shippers manually log into each retailer's appointment portal to create and update appointments. This AI agent handles the portal interaction autonomously, eliminating hours of manual data entry across customer systems. The intelligence layer is what creates the gap. The basic capability is buildable. Building it on top of 11 years of cross-company supply chain intelligence, with continuous learning from 2.5 million agent actions per month, is what cannot be replicated with software alone.
Order Twin, Shipment Twin, Appointment Twin
Alan executes the workflow. Every action recorded with full decision trace.
Cross-company intelligence powering every decision
Custom Insights: Customer appointment compliance dashboard; FourSight AI: "How many customer appointments are at risk this week?"
Customer Appointment Automation
- Customer Pickup Scheduling Automation
- Cross-Dock Orchestration
- Appointment Reschedule Automation
Validation
Deployment Evidence
Expected Impact Range
Related outcomes
Lower OTIF penalties and protect revenue by catching at-risk shipments early instead of disputing chargebacks after the fact.
Penalty claims validated and disputed with evidence in minutes, not hours — recovering costs that would otherwise go unchallenged.
OS&D claims processed in minutes with evidence-backed resolution recommendations.
One billion hours of operational work completed by AI agents over the next decade.
