Learn how Iguazio provided Quadient with an out-of-the-box data science platform and next-level MLOps automation capabilities, saving their data scientists and developers precious time and resources
Artificial Intelligence is revolutionizing the manufacturing industry, resulting in great advancements and gains in quality, productivity and cost reduction. Innovative manufacturers that embrace AI are transforming the way they do business – and their bottom line.
The Iguazio Data Science Platform for Manufacturing enables you to develop, deploy and manage AI applications, transforming AI projects into real-world business outcomes. With Iguazio, you can build and run AI models in real time, deploy them anywhere (multi-cloud, VPC or on-prem), and bring to life your most ambitious data-driven strategies for demand forecast, quality management and streamlined production processes.
Predict demand accurately to eliminate waste and ensure that your customers are always satisfied.
Detect malfunctions before they occur and prevent them by taking automated actions to save precious time and keep processes running smoothly.
Optimize your manufacturing schedule by harnessing data from the edge as well as historic and current market data.
Track and model the quality of your products to detect issues as they occur and improve the quality and overall yield.
“Iguazio provides a distributed cloud near the edge for the greater simplicity, performance, security and agility required by next generation applications.”
RBVC Technology Managing Director
"Iguazio provides an additional path to run AI on the edge beyond our current Microsoft Azure Machine Learning inferencing on the edge."
Principal Group Product Manager
Iguazio worked with a large multi-national customer to detect signals of impending equipment malfunctions in real-time. Using real-time data from sensors, correlated with historic data and manufacturing logs, thousands of ML models were set up and managed. These models learned to cater to different types of equipment and predict malfunctions of different types. Users could also define different types of false positives to improve model accuracy.