Keep your flexibility and data sovereignty. ARES comes as software-as-a-service or can be self-hosted in any cloud or on-premise.
Benefit from our easy-to-use dashboards to model directly or integrate predictions and optimizations into your existing work flows.
Predictions are just the first step. Automatically optimize the input values of your use-case to reach the targeted output.
Get to know concrete user scenarios and added values through
Predictive Quality and Process Optimization in production.
Get a first impression of how easy it can be to analyze, predict and optimize process data with Iconpro ARES in days, not months.
What is AutoML?
AutoML, short for Automated Machine Learning, refers to the use of automated tools and algorithms to automate the process of machine learning. The goal of AutoML is to simplify access to machine learning for users who do not have extensive data analysis or programming skills. With AutoML platforms, it is possible to build, train and evaluate models without deep machine learning expertise.
What are the benefits of AutoML?
The benefits of AutoML are many. They include accelerating model development, lowering the barrier to entry for the use of machine learning, improving model quality through automated prediction and optimization, and reducing model configuration errors. In addition, AutoML enables faster implementation of data-driven and, where appropriate, automated decisions and optimizations in processes.
What are application examples for AutoML?
In production processes and quality control, AutoML can be used to create predictive quality models that predict when and why quality problems might occur. This enables proactive measures to prevent defects. In process optimization, AutoML helps optimize parameters and operations to increase production efficiency and quality.
What is MLOps?
MLOps, or Machine Learning Operations, is an area focused on managing and scaling machine learning models in production environments. It includes automating model deployment, monitoring, maintenance and updating. MLOps aims to bridge the gap between model development and actual implementation in business applications.
What are use cases for MLOps?
In the area of manufacturing processes, MLOps enables the operational integration of prediction and optimization algorithms into the continuous monitoring of machines and systems to predict failures and schedule maintenance. It can also, in the same way, improve automated control of production processes to avoid bottlenecks and increase efficiency.
How are AutoML and MLOps related?
AutoML and MLOps complement each other in the development and implementation of machine learning models. AutoML enables rapid model creation and optimization, while MLOps ensures that these models can be effectively deployed in production environments. Combined, they enable a seamless process from model development to real-world application, facilitating and maximizing the use of machine learning in enterprises.
Testimonial Festo SE & Co. KG
Aufgrund seiner Erfahrung ist IconPro ein zuverlässiger Partner für Machine Learning Software, die den tatsächlichen Bedürfnissen in der Produktion entspricht.
IconPro Apollo erweist sich als intelligente, vernetzte und produktive Lösung für die smarte Überwachung von Messmaschinen.