How Arneg has been innovating in the market for the last 60+ years

Arpan Sharma

07 Jun 2025 — 4 min read

In the highly competitive field of commercial refrigeration, operational efficiency and minimization of downtime are crucial. Arneg SpA (Arneg), needed a transformative solution to shift from a reactive to a proactive customer service model. Arneg aimed to enhance its support capabilities by integrating generative AI in customer service, ensuring seamless operations and improved customer interactions.

Arneg is a global leader in advanced refrigeration solutions and is renowned for its innovative, energy-efficient, and eco-friendly products. Catering to supermarkets, convenience stores, food service, and industrial applications, Arneg delivers high-quality refrigerated display cases, cold rooms, and custom solutions.

Their commitment to sustainability, technological excellence, and customer satisfaction ensures top performance and reliability. With a worldwide presence and a dedicated team, Arneg continuously drives innovation, providing localized solutions and exceptional service to businesses globally.

To achieve a proactive customer service model, Arneg leveraged advanced Artificial Intelligence (AI) and Internet of Things (IoT) capabilities to create a predictive maintenance model that would significantly elevate their service standards. The integration of generative AI in customer service further supported this transformation, optimizing customer interactions and streamlining support processes.

Industry Overview and Challenges

The commercial refrigeration industry faces numerous challenges, including stringent service-level agreements, round-the-clock customer support, and maintaining high food safety standards. Reactive maintenance approaches often lead to higher costs and inefficiencies, as service teams are only called upon when problems have already caused disruption.

Specific Industry Challenges:

Service Downtime: Any malfunction can lead to food spoilage and significant financial losses.
High Operational Costs: Reactive maintenance demands an immediate response, leading to escalated costs.
Regulatory Compliance: Strict adherence to food safety regulations requires reliable and efficient refrigeration systems.

Problem Statement

To maintain its competitive edge and provide superior customer service, Arneg required a failure-tolerant, scalable system that could predict maintenance needs and prevent downtime. The existing local Interactive Remote Information System (IRIS) was inadequate for the evolving demands. The challenge was integrating a robust, scalable cloud solution with AI capabilities into its infrastructure and generative AI in customer service to enhance overall support efficiency.

Solution Provided

Arneg developed an advanced predictive maintenance system, integrating their IoT infrastructure with AI-driven tools specifically, SageMaker and Forecast.

Use Case: Predictive Maintenance

Predictive maintenance utilizes AI to predict when a piece of equipment will fail so that maintenance can be done just in time to prevent this failure. This approach turns unscheduled downtime into scheduled downtime, thus reducing operational disruptions and costs. Additionally, the incorporation of generative AI in customer service ensured prompt and efficient handling of customer queries and issues.

Technologies and Tools

SageMaker: To build, train, and deploy machine learning (ML) models quickly.
Forecast: For delivering highly accurate forecasts using ML.
IoT Infrastructure: For collecting data such as temperatures, energy consumption, and failure metrics from refrigeration units.

Solution Architecture

Data Collection: IoT devices in refrigeration units collect data (e.g., temperatures, energy consumption).
Data Standardization: This data is sent to the cloud where it is standardized and homogenized.
Machine Learning Models: These standardized datasets are used to build predictive models in SageMaker and Forecast.
Maintenance Alerts: The models predict potential failures and issue notifications to maintenance teams, allowing for proactive service.

Implementation Challenges

Data Handling: Standardizing and homogenizing vast amounts of IoT data.
Scalability: Ensuring that the system can handle data collection from a global network.
Accuracy: Achieving a predictive accuracy rate that was high enough to provide reliable service.

Results Achieved

Key Metrics:

Predictive Accuracy: Achieved more than 80% accuracy in predicting maintenance needs.
Data Throughput: Capable of collecting and processing 11 million IoT records daily.
Response Time: Significant increase in the efficiency of reactive protocols, paving the way for a proactive maintenance strategy.

By implementing this solution, Arneg was able to:

Reduce Downtime: By predicting and addressing issues before they become critical.
Cut Operational Costs: By minimizing emergency maintenance and optimizing resource allocation.
Improve Service Quality: Providing preemptive solutions enhanced customer satisfaction and trust, further supported by generative AI in customer service.

Broader Implications for the Industry

The success of Arneg’s predictive maintenance system highlights the transformative potential of AI in the commercial refrigeration industry. Such advancements are not limited to this sector but can be applied across various industries facing similar challenges. The integration of generative AI in customer service also presents significant opportunities for enhancing customer interactions across different sectors.

Common Challenges AI Can Solve:

Predictive Analytics: For equipment maintenance across manufacturing, automotive, and healthcare industries.
Operational Efficiency: AI can help in optimizing supply chain logistics, managing energy consumption, and more.
Customer Service: Generative AI in customer service can automate and streamline customer interactions, reducing human error and improving response times.

How Vibencode Can Help

At Vibencode, we specialize in generative AI solutions that drive business value across industries. Our team of experts can tailor solutions to your specific business needs, leveraging cutting-edge technologies to transform your operations and enhance efficiency. Understanding the future of AI in customer service is crucial for staying competitive and innovative.

Our Offerings:

Custom AI Solutions: From predictive maintenance to customer service automation.
Data Analytics: Comprehensive tools for data collection, standardization, and real-time processing.
Consulting Services: Expert guidance through every step of your AI journey.

Conclusion

Arneg’s transition to a predictive maintenance model underscores the profound impact AI can have on operational efficiency and customer service. By harnessing the power of AI, Arneg not only improved its service quality but also set a benchmark for the industry.

As businesses look to innovate and stay ahead of the curve, partnering with AI experts like Vibencode can make all the difference. For more insights or to explore how AI can transform your business, visit our website at www.vibencode.com

Incorporating generative AI in customer service and understanding the future of AI in customer service will be crucial in maintaining a competitive edge and achieving long-term success.