#3: Automating 80% of truckload appointment scheduling with an AI agent
Learn how we built an AI agent to automate one of the most painful workflows in trucking: appointment scheduling. And why the foundation of that agent will help us automate a lot more workflows.
If you work in freight, you know appointment scheduling is a full-time job. Every shipment requires you to schedule at least one appointment, usually two, to make sure when the truck shows up at each facility you are able to swiftly pick up / drop off and keep things moving.
Compounded across thousands of shipments per month, this means many thousands of human emails that teams field day in and day out going back & forth to schedule appointments. Tons of errors, delays in responding, and typing information back into your TMS to make sure everyone in the value chain knows when the appointments will happen.
The pain:
Scheduling is high volume, repetitive, error-prone and time-sensitive. And because it’s one of those workflows that touches every shipment, even a small mistake can snowball into delays, missed appointment windows, and failing your customer commitments.
Specifically, this workflow is painful because:
Results in thousands of manual emails every week.
Lots of waiting around for replies from facilities.
Mistakes: someone forgets to confirm, replies get lost, or details don’t get entered correctly.
Delays: if one appointment falls through, a truck can sit for hours, or completely miss its delivery window.
What we built
Instead of adding headcount or buying another scheduling tool, we built an AI agent in-house to handle the back-and-forth for us. Think of it as a junior operations hire who only schedules freight, works 24/7 in English and Spanish, and never misses an update.
The AI agent reads inbound emails, figures out if they’re a confirmation, a reschedule, or a request for more info, and takes the right next step based on our SOPs. It can lock in the time with the facility, update NuvoOS so everyone stays in the loop, and also knows when not to take action and flag something for human review.
When action is needed, it passes the job to specialized sub-workflows:
Initial request workflow: Generates and sends the appointment request email using GPT-4o for natural language generation and formatting.
Reply handling workflow: Uses Gemini 2.0 Flash for classification, paired with GPT-4o for time extraction and slot selection, to confirm the best appointment in English or Spanish.
Logging workflow: Updates appointment details directly in NuvoOS via API, labels the email thread for reference, and provides a short summary of actions taken. This gives Ops teams visibility without having to review the full email thread.
Before we let it touch live freight, we stress-tested it with thousands of real and synthetic emails. We used Gumloop to batch test multiple LLMs, GPT-4o, Claude 3.5 Sonnet, and Gemini 2.0 Flash, against messy edge cases like multi-stop changes, vague confirmations, and even intentionally misleading responses, to make sure it could pick the right action or know when to call in a human.
Every step the agent takes shows up in a dashboard, so our operations team members can see what it’s about to do and why.
The results:
The agent handles about 80% of the scheduling process end-to-end with zero human touch. The other 20% still requires escalations & operations team reviews, usually because the facility’s email was unclear, unrelated, or required a judgment call.
Freed up about a full day of work (~8 hours) per rep every week, which means more time solving real problems for our customers.
Fewer delays, faster escalation when something goes wrong, and the same accuracy whether it’s the first load of the day or the hundredth.
Agent works both for cross-border US-MX-CAN shipments which are more complex, and also for intra US freight shipments which are simpler.
Path to 95%+ automation: Every time the agent flags an exception, we feed the solution back into the model for training and continuous improvement. That's how we move toward high-90% accuracy without losing a human in the loop for the real exceptions that AI cannot yet handle.
This foundation will allow us to extend the same architecture to tons of other workflows like carrier dispatch check-ins, driver info collection, capacity confirmation and bid collection.
If you want a demo of our AI appointment scheduling agent or of Nuvo OS (our AI native operating system for North America freight), please book some time with our team here.
We’re always excited to share any of our learnings and how we are helping North American shippers reduce freight spend, boost customer service levels, and adopt AI across their entire North America supply chain.