What happens when a bustling warehouse faces hours-long truck queues, delayed shipments, and manual paperwork that slows everything down? For one of the world’s leading bottling companies, this wasn’t just a logistical hiccup—it was a daily disruption impacting their supply chain’s efficiency and bottom line.
With hundreds of trucks arriving and departing across multiple warehouse facilities, the manual truck pre-check-in process became a serious operational roadblock. Drivers were handed clipboards instead of tablets, queues stretched endlessly, and dock assignments relied on manual scheduling—causing:
- Long wait times and idle truck hours
- Data inaccuracies due to human error
- Poor visibility into truck flow and dock utilization
Applying its Standard Digital Framework, Acuvate introduced a transformative solution powered by machine vision and generative AI. With a custom ML-MV model, the pre-check-in experience for our customer evolved from pen-and-paper to real-time precision—drastically reducing manual intervention, improving dock throughput, and enhancing data accuracy.
This blog unpacks how Acuvate turned a costly pain point into a digital advantage to the customer—streamlining operations and setting the foundation for intelligent supply chain transformation. Ready to reimagine logistics? Let’s dive in.
Acuvate’s Fully Automated Truck Pre-Check-In Solution
In high-volume warehouse environments, every minute matters. For our customer, extended truck wait times due to manual scheduling and dock assignments weren’t just a minor delay—they translated into increased fuel costs, driver overtime, and missed delivery windows. Meanwhile, data inaccuracies from handwritten forms led to billing disputes, incorrect shipment logs, and logistical blind spots. Even worse, the lack of visibility into real-time truck movement created a domino effect—dock spaces sat underutilized, dispatches were misaligned, and warehouse throughput was compromised. These compounding inefficiencies not only strained operations but threatened customer satisfaction and supply chain agility.
1. Acuvate’s Comprehensive Solution
To overcome these challenges, Acuvate deployed a custom-built Machine Vision (MV) model integrated into the Acuvate Data framework. Installed at warehouse entry points, Axis cameras streamed real-time footage. The solution consisted of:
- Real-Time Analytics: Video feeds were analyzed in real-time and processed on Nvidia devices for edge computing. This model allowed the system to automatically recognize truck types, capture license plate numbers, and log arrival timestamps instantly and accurately, ensuring immediate insights and zero latency.
- Automated Data Integration: The solution was integrated with the customer’s Oracle Warehouse Management System and a pre-check-in app, ensuring seamless flow of truck data.
- Driver-Friendly Interaction: Through a chatbot-enabled web app and SMS system, drivers completed pre-check-ins without touching a clipboard—reducing manual steps to zero.
Scalable Cloud Infrastructure: Deployed via Microsoft Azure, the system ensured high availability and could scale effortlessly across multiple warehouse locations.
The result? A fully automated truck pre-check-in solution that brought real-time visibility, reduced human error, and unlocked significant gains in efficiency & cost savings—turning a bottleneck into a competitive edge.
Acuvate Implemented its Solution with a Structured Approach
Behind every transformative solution lies a meticulous execution plan — and Acuvate’s approach to streamlining the truck pre-check-in process for the bottling giant was no exception. After identifying key bottlenecks and designing an AI-powered vision for the future, the real challenge was translating that vision into an on-ground reality. Here’s how Acuvate made it happen:
- The implementation methodology began with a comprehensive device assessment, ensuring that the selected edge devices and cameras were not only cost-effective but also met the specific operational needs of the warehouses.
- Next came custom model development — deep learning algorithms were trained to deliver high accuracy, even under fluctuating weather and lighting conditions, ensuring dependable performance round the clock.
- User accessibility was prioritized through an intuitive interface design, offering multiple access points tailored to varying levels of digital maturity among truck drivers.
- The team then orchestrated a robust infrastructure setup, deploying high-definition Axis cameras at strategic entry and exit points to capture essential video feeds.
- Seamless system integration followed, connecting all backend components into a unified platform for real-time visibility.
- Finally, a pilot rollout paved the way for large-scale adoption. Leveraging DevOps principles, the solution was rapidly scaled across the customer’s warehouse network — delivering efficiency, accuracy, and speed at every checkpoint.
From Bottlenecks to Breakthroughs: Tangible Results and Lasting Business Impact
When Acuvate’s machine vision and generative AI solution went live, the transformation didn’t just unfold—it accelerated. What was once a manually intensive, error-prone pre-check-in process evolved into a streamlined, data-driven system that delivered measurable results.
1. Remarkable Results That Redefined Efficiency
With automation at its core, the solution brought 95% data accuracy, eliminating the manual errors that once plagued the check-in logs. This level of precision wasn’t just a technical milestone—it reshaped daily operations, offering cleaner, actionable insights.
Efficiency soared, with manual intervention reduced by 60–70%, allowing ground staff to shift their focus from routine checks to more strategic warehouse functions.
One of the most visible wins came in the form of cost reduction. With truck wait times significantly trimmed, fuel costs, demurrage charges, and labour hours saw a steep drop—unlocking substantial financial savings.
The scalability of the solution was equally compelling. Its modular design and cloud-native architecture made it easy to replicate across multiple warehouse locations—without incurring major infrastructure investments.
2. Strategic Business Impact That Set the Stage for the Future
Beyond operational wins, the customer experienced deep, strategic shifts. Latency reduction across the system improved truck turnover rates, directly boosting warehouse throughput and delivery timelines.
Enhanced traceability and accountability added a new layer of confidence. Every truck movement and timestamp was captured and stored, ensuring a robust audit trail and improved governance over logistics operations.
Through intelligent data flows, the solution unlocked predictive capabilities, enabling the forecasting of dock availability and optimizing workforce allocation.
Crucially, the implementation created a future-ready digital backbone. With this framework in place, the customer is now well-positioned to adopt next-gen features like post-check-out tracking, AI-driven scheduling, and integration with broader supply chain platforms—turning today’s success into tomorrow’s advantage.
What began as a challenge in streamlining truck pre-check-ins evolved into a blueprint for digital transformation. By harnessing Acuvate’s comprehensive data services—from seamless data collection to real-time processing and intelligent analysis—the customer unlocked new levels of operational efficiency and strategic foresight. This initiative stands as a powerful example of how AI, ML, and machine vision can reimagine legacy logistics processes, driving measurable impact and scalable innovation across the logistics & supply chain industry.
Check out the detailed case study for this customer here!
Are you also looking forward to transforming your logistics operations with such a solution?
