Smart Machines for High-Availability Industrial Operations

The Challenge

The company faced three critical challenges that resulted in high resource consumption and loss of operational efficiency:

• Lack of visibility: Critical equipment operating without advanced telemetry, which prevented correlating data across production lines and detecting anomalies in time.
• Reactive maintenance: High operational costs due to unplanned downtime, urgent interventions, and slow response times.
• Need for a scalable digital model: Legacy systems did not allow the integration of Artificial Intelligence (AI) or the agile replication of solutions to other plants.

The Solution: AI at the Edge and Readiness for Physical AI

To address this scenario, GALEO designed and deployed an end-to-end industrial platform built on AWS services. The architecture is based on bringing computing power and decision-making capabilities directly to the plant floor:

Artificial Intelligence at the Edge: Through the installation of Industrial PCs equipped with AWS IoT Greengrass and OPC-UA connectivity, the platform not only monitors in real time, but also moves AI model inference directly to the network edge. This enables ultra-fast, early detection of anomalies in critical machinery locally, and automates alerts without depending on cloud latency.

The Leap Toward Physical AI: By consolidating a distributed architecture where data and algorithmic models coexist on the production line itself, the plant establishes the perfect digital baseline to support the Second Wave of AI (Physical AI). The system is ready to host future AI-intensive use cases at the Edge, allowing intelligence to evolve from being a mere recommender to becoming an agent that can act directly on the environment and physical machines.

Business Impact (C-Level KPIs)

The transformation from reactive maintenance to a data-driven operation has delivered the following results:

• +15% in equipment availability.
• -50% in response time to anomalies.
• -40% in fault diagnosis time.
• -30% reduction in critical plant incidents.

Qualitative Results

• Operations teams now act before failure occurs, not after.
• Maintenance is planned based on actual equipment condition, not by calendar.
• The plant has a digital baseline to scale industrial AI.
• Operational risks and costs associated with unplanned downtime are reduced.

Value Architecture

• Security guaranteed by AWS.
• Controlled costs and immediate scalability.
• Integrable with corporate systems (ERP, CMMS, OT).
• Ready to expand to new lines or plants.

Customer Review

“The implementation of a cloud platform has enabled us to evolve toward more autonomous systems, improving error detection, real-time monitoring, and operational efficiency. The result is a smarter solution that reduces effort, anticipates incidents, and delivers greater value to the business.”