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2021: Integration with Azure Machine Learning

On November 10, 2021, the company Seeq announced the launch of additional integrated support. algorithms machine learning Microsoft Azure Machine Learning The Seeq Azure extension allows manufacturing companies to deploy machine learning models from Azure Machine Learning as extensions through Seeq Workbench. As a result, the implementation of machine learning algorithms and innovations developed by IT subdivisions will allow OT specialists of the first line of support to optimize the process of making their decisions and optimize production indicators, indicators of sustainable development and business results.

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As reported, Insight Ventures, Saudi Aramco Energy Ventures, Altira Group, Chevron Technology Ventures, Cisco Investments and other investors have already invested more than $100 million in Seeq. The Seeq machine learning strategy provides for end users to access algorithms from various sources, including open source codes, as well as from third-party and internal data processing and analysis groups.

With the integrated Azure Machine Learning solution, data processing and analysis teams can develop models using Azure Machine Learning Studio, and then publish them through the Seeq Azure extensions, which became available on the GitHub in November 2021. With the help of Seeq Workbench, first line support professionals with expertise can access these models, confirm them by superimposing operational work data on the model results and send a response to the data processing and analysis team. This facilitates iterative interaction between IT and OT specialists, optimizes the time to understand the essence of the issue for both groups, while creating the process of continuous improvement necessary to maintain the life cycle of machine learning operations.

Seeq and Azure Machine Learning are critical add-on solutions for implementing the machine learning model lifecycle. Leveraging the strengths of IT and OT users, the Seeq Azure feature enhances interaction with Seeq and enables companies to optimize the scope of model development and implementation. told Megan Buntein, Director of Cloud Partnerships at Seeq

Through this integration, independent Seeq applications allow first-line support specialists to independently perform special analyses and use models, rather than relying on support from a member of the data processing and analysis group. As you get results with Seeq models, allows users to scale models across the company for reliability, optimization, monitoring, and sustainability. In addition to launching Azure integration, Seeq is also expanding its list of published open source algorithms this week, adding an extension to the GitHub designed to search for multi-variable structures. The Seeq Open Source Solution Gallery also contains algorithms and work cycles for correlation and cluster analysis that users can modify and optimize for their needs.

The Seeq solution has been available on Azure Marketplace as an SaaS application since 2019, with support for a large number of Azure cloud services, including Synapse, Azure Data Lake and Active Directory. Seeq also supports connectivity to Azure Data Explorer, Time Series Insights, and Power BI. Seeq solutions are distributed worldwide by a global network of systems integrators who provide training and resell Seeq products in more than 40 countries in addition to direct sales in North America and Europe.