Fero Labs: Together we'll build a sustainable tomorrow
Digitalization
The Enduring Relevance of ‘GIGO’ in the Age of AI
For process engineers and data scientists: Poor data quality can derail industrial AI. Discover why "Garbage In, Garbage Out" (GIGO) remains critical in industrial process workflows using AI. Learn how poor data quality impacts process optimization and predictive models, and explore actionable strategies to ensure reliable insights for manufacturing success. Explore how Fero Labs tackles GIGO with advanced tools to clean, curate, and optimize manufacturing data for actionable results.
Fero Labs Named to Fast Company’s Annual List of the World’s Most Innovative Companies of 2025
Press Release: Fero Labs has been recognized on Fast Company's prestigious World's Most Innovative Companies of 2025 list. This accolade highlights Fero Labs' commitment to enhancing manufacturing processes through explainable industrial AI, empowering engineers and metallurgists to make faster, easier decisions for profitability and sustainability. Fero Labs joins ranks with tech giants like Waymo, Nvidia, and Duolingo on the prestigious list. Fero Labs was previously honored in 2024 as a World Economic Forum Technology Pioneer and Gartner Cool Vendor. Fero Labs continues to drive innovation in sustainable and profitable manufacturing, solidifying its position as a leader in industrial AI technology.
7 Ways Fero Labs AI Streamlines Industrial Engineers' Work
This article reveals 7 ways Fero Labs AI streamlines a process engineers' workflow. From pinpointing root causes 90x faster to automating complex data analysis of hundreds of process readings in minutes, our platform saves you time. Explore how AI-driven quality forecasting and digital twin simulations optimize processes and cut costs.
How Early Detection Fero Alerts Prevent Issues to Avoid Failures
Data-driven process engineers use Fero Alerts for early anomaly detection in manufacturing. This article explains how the Fero AI suite provides real-time anomaly alerts, detailed AI-powered diagnostics and root cause analysis, and a simulated digital twin to prevent production failures.
