Representative End User Clients
Representative Automation Clients
Representative Software Clients
Uptake announced its launch of a new product called Uptake Scout - The Data Science Studio that puts all the tools to create state-of-the-art industrial analytics into the hands of customers. Uptake's platform currently powers thousands of pre-built data science models, but now Uptake Scout allows users to quickly and intuitively configure and deploy custom models and automated anomaly detection alerts. Uptake Scout has a simple and intuitive user interface. Coding or advanced statistics skills are no longer required to access the value hidden in industrial data.
With Uptake Scout, the burden of collecting, cleaning, and organizing data is automated using sophisticated machine learning and artificial intelligence tools like natural language processing. When data is well-prepared for analytics, it allows analysts to focus on the activities that generate the most value for their organization.
Users can explore historical data across all types of data, equipment, and locations. Based on business-specific use cases, historical data can be used to identify, create, and test user-defined alerts - detecting anomalies from simple thresholds to complex multivariate conditions. Once an alert is defined, it is tested on historical data to ensure the frequency of alerts and reliability of the insights are viable.
As a result, users are able to leverage their data to enhance and customize their condition monitoring process, retain invaluable expert knowledge, and leverage a single source of truth across all business units, locations, and asset types.
Michael Guilfoyle, ARC Advisory Group, commented, "Uptake is ensuring it is aligned with the direction of the market with the addition of Uptake Scout to existing apps Uptake Compass and Uptake Radar. Together with machine learning and artificial intelligence, modern cloud-based application development and runtime platforms are changing the industrial software marketplace.
"Uptake's overall strategy reflects the shift in demand from users toward ready-to-deploy AI that leverages pre-trained industrial machine learning. Providers that initially delivered AI platforms for industrial intelligence are now delivering outcome-based applications powered by industry expertise. For many industrial users, it's a straighter line to initial value."