Scaling Industrial AI in Samarco's OT: Lessons from Samarco's experience at ABM Week 2025

TL;DR;

For the second consecutive year, Aignosi had the privilege of participating in ABM Week 2025 the largest technical event for the steel and mining value chain in Brazil.

This edition was particularly meaningful: together with our partner Samarco, one of the biggest mining companies in Brazil, we presented a peer-reviewed technical paper at the conference — a milestone that highlights how Artificial Intelligence is creating measurable impact in complex operational environments.

From Concept to Production: Virtual Sensors in Mining Operations

The paper, “Scaling AI and Machine Learning in Samarco’s OT”, describes how two virtual sensors, developed and deployed in Samarco’s iron ore operations, are driving operational efficiency:

Real-time mass flow estimation on conveyor belts, eliminating the need for additional instrumentation.
Silica content prediction in rougher flotation, directly feeding advanced controllers to optimize recovery.

These models are not experimental. They are in production today, automatically retrained, with end-to-end observability and running fully on-premise to meet OT cybersecurity and latency requirements.

Scaling AI in OT: A New Benchmark

The deployment of these virtual sensors was made possible through our SIENTIA™ Industrial AIOps platform, which enabled:

• 15 models deployed in less than 3 months
• A governance framework ensuring security and reliability
• A scalable foundation for future AI use cases

Looking ahead, Samarco plans to scale to around 50 models by the end of 2025, consolidating one of the largest industrial AI initiatives in OT environments in Brazil.

This demonstrates that scaling AI in heavy industry is not just aspirational — it is achievable, when rooted in operational reality.

Key Insight: Scaling Starts with What Works

A critical lesson from this journey: scaling AI in industry doesn’t start with deep learning. It starts with virtual sensors that work — and work well.

When organizations deploy 15 models in less than 90 days — and project 50 by year’s end — it signals more than technological advancement. It shows real impact in industrial operations: fewer unplanned stoppages, higher process stability, and improved productivity.

Gratitude and Collaboration

We thank Samarco for leading this work, especially Jeancarlo, whose vision and leadership were instrumental throughout this transformation.

It was also an honor to share this achievement with professionals and companies shaping the future of the industry, including colleagues from Vale, Stefanini IHM, Usiminas, and all who contributed to the technical discussions at ABM Week.

 Conclusion

Industrial AI is no longer a distant promise. As Samarco’s journey shows, it is scalable, sustainable, and operationally impactful — even in environments with the strict constraints of OT.

The path forward is ambitious, but the foundation is clear: governance, scalability, and trust in AI systems that deliver measurable value.