The UK’s biggest logistics conference, Multimodal, is a showcase of the industry's future. For many, that future is still a roadmap of concepts and promises. So, when we decided to demo our AI voice agent live on the main stage, some saw it as a risk. What if it failed? What if the audience's scenario was too complex?
We saw it differently. If we aren't confident enough to put our technology to an unscripted, public test, why should our customers trust it with their operations?
Last week, we put that confidence into action. No scripts, no pre-recordings. We invited the audience to throw their real-world, daily headaches at our AI agent. This isn't just about technology; it's about solving the persistent, frustrating problems that plague logistics.
The Challenge: A Live, Unscripted Logistics Crisis
The daily life of a logistics operator is one of constant "firefighting." A delayed driver, a closed gate, a documentation error—each issue triggers a cascade of manual tasks: phone calls, emails, and frantic updates to the Transportation Management System (TMS).
We asked the audience for a typical scenario. One that came up was a classic: “A driver is running late due to an unexpected sustainability protest blocking the road.”
This single event creates a chain reaction of necessary actions. Here’s how our AI voice agent managed the entire workflow, live on stage, in real-time:
1. Automated Data Retrieval: The moment the potential delay was flagged, the AI agent instantly queried the TMS to pull the driver's ETA and all relevant load details. It had the full context in milliseconds.
2. Proactive Driver Communication: The AI agent initiated an outbound call to the driver. Using conversational, natural language, it asked for a status update. "Hi, this is the AI assistant from Axe. I see you're on load 74B. We're showing a potential delay on your route. Can you confirm your status?"
3. Dynamic Information Capture: The audience provided the reason: "stuck in a protest." The AI captured this specific reason, asked the driver for a new estimated ETA, and logged the unstructured verbal information.
4. System-Wide Updates: This is where the magic happens. The AI didn't just store the information, it acted on it.
It *updated the TMS** with the new ETA and the reason code for the delay.
It sent an *automated alert to the operations team’s Microsoft Teams channel**, notifying them of the situation without anyone needing to check a dashboard.
It triggered an *email notification to the end customer**, proactively managing their expectations.
A complex, multi-step problem that would have taken an operator 15-20 minutes of calls and manual data entry was resolved, end-to-end, in under two minutes. This is a call logistics teams make thousands of times a month, and it is now fully automated.
Beyond a Single Task: AI as a Digital Co-Worker
What we demonstrated at Multimodal wasn't just a fancy chatbot. It was an example of an AI Digital Worker. This is a crucial distinction. Our AI doesn't replace your core systems like your TMS, load boards, or telematics. It integrates with them.
Think of it as the ultimate co-worker. It pushes and pulls data between your fragmented systems, eliminating the need for a human to act as a bridge. This "system of systems" approach ensures:
* A Single Source of Truth: Data is consistent across all platforms in real-time.
* Reduced Human Error: Manual data entry mistakes are eliminated.
* True Scalability: You can increase your operational capacity without a linear increase in headcount. Our data shows we eliminate over 70% of manual back-office work, saving teams more than two hours per person, per day.
The Financial Impact: From Efficiency to Profitability
Streamlining operations is only half the story. The ultimate goal is to improve financial performance. By automating repetitive communication and administrative workflows, AI directly impacts the bottom line:
* Margin Improvement: Automating rate negotiation, optimizing dispatch based on real-time data, and reducing operational overhead can improve margins by up to 15%.
* Revenue Growth: With AI handling thousands of inbound quote requests and outbound carrier calls simultaneously, 24/7, you capture more opportunities and convert leads faster.
* Enhanced Customer Service: Proactive, instant communication builds trust and retention, turning customer service from a cost center into a competitive advantage.
The Future is Now
The enthusiastic response at Multimodal confirmed what we already knew: the logistics industry is ready to move beyond inefficiency. The era of being stuck on repeat—making the same calls, sending the same emails, and keying in the same data—is over.
AI is transforming the back office from a bottleneck into a powerhouse of efficiency and intelligence. Companies that embrace this shift today are not just adopting new technology; they are building the foundation to become the industry leaders of tomorrow.
Want to see how our AI can automate your most repetitive tasks?
Get in touch for a personalised demo.
James McElroy | CEO & Co-Founder | [email protected]
Dan Quill | CTO & Co-Founder | [email protected]
