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Seeq Software

Seeq Corporation

Seeq Software

Seeq Corporation

Seeq is an advanced analytics software for process manufacturers that enables shared insights.

Seeq is an industrial time-series data virtualization, collaboration, and analytics platform hosted on Microsoft Azure Cloud that empowers plant engineers, operators, data engineers, and data scientists with advanced applications to improve operational performance.

The suite of applications is self-service and enables process manufacturing subject matter experts and their IT colleagues to collaborate and perform analyses leveraging common data sets, calculations, and models, to address a limitless number of industrial time-series focused use-cases to improve production, quality, reliability, and meet sustainability goals.

Seeq aligns both OT and IT data and persona silos. Subject matter expert feature engineered time-series data sets can be integrated with cloud services like Azure Data Explorer, Azure Data Lake, Azure SQL, Azure Machine Learning, Azure Databricks, PowerBI, etc. for broader platform initiatives and collaboration with data scientists for ML/AI development.

More about Seeq:

-Seeq Workbench: Workbench is Seeq’s application for engineers engaged in diagnostic, descriptive, and predictive analytics with time process manufacturing data. It includes features to expedite the full arc of the analytics process, from connecting to historians to data cleansing, visualization, modeling, and calculations.

-Seeq Organizer: Organizer is Seeq’s application for engineers and managers to assemble and distribute Seeq analyses as reports, dashboards, and web pages. Organizer “Topics” may include text, images, scorecard items, visualizations generated in Seeq Workbench (charts, scatter plot, tree map, etc.), and other content.

-Seeq Data Lab: Data Lab is Seeq's application for process engineers to expand their Seeq analytics efforts to the rich ecosystem of Python libraries, and data scientists can participate directly in industrial analytics by leveraging Seeq for data access, cleansing, modeling, and other featur