(MENAFN- Mepax) Seeq Corporation, a leader in manufacturing and Industrial Internet of Things (IIoT) advanced analytics
software, announces the expansion of its efforts to integrate machine learning algorithms into Seeq
applications. This will enable organizations to operationalize their data science investments, open source
and third-party machine learning algorithms for easy access by front-line employees.
Seeq customers include companies in the oil & gas, pharmaceutical, chemical, energy, mining, food and
beverage, and other process industries. Investors in Seeq, which has raised over $100M to date, include
Insight Ventures, Saudi Aramco Energy Ventures, Altira Group, Chevron Technology Ventures, and Cisco
Investments.
Seeq’s strategy for enabling machine learning innovation provides end user access to algorithms from a
variety of sources rather than forcing users to rely on a single machine learning vendor or platform. This
addresses the diversity and types of algorithms available to organizations, including:
-Open sources algorithms and other public resources. For example, this week Seeq will publish two Seeq
Add-ons to GitHub, including algorithms and workflows, for correlation and clustering analytics, which users
can modify and improve based on their needs.
-Customer-developed algorithms in Seeq Data Lab—or machine learning operations platforms such as
Microsoft Azure Machine Learning, Amazon SageMaker, Anaconda, and others—as part of data science or
digital transformation initiatives.
-Third party algorithms provided by software vendors, partners, and academic institutions. AWS’s Lookout for
Equipment, Microsoft Azure AutoML, BKO Services’ Pump Prediction, and Brigham Young University’s
open-source offerings are examples of the emerging marketplace for industry and vertical market specific
algorithms.
The Seeq initiative also address the critical ‘last mile’” challenge of scaling and deploying algorithms in
manufacturing organization by putting data science innovation in the hands of plant employees in easy-touse
applications: Seeq Workbench for advanced analytics, Organizer for publishing insights, and Seeq Data
Lab for ad hoc Python scripting.
This is in addition to Seeq support for the foundational elements of success with machine learning. This
includes access to all manufacturing data sources—historian, contextual, and manufacturing
applications—for data cleansing and modeling, support for employee collaboration and knowledge capture,
quick iteration, and enabling performance-based continuous improvement workflows.
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“Data science innovation in manufacturing organizations has the potential to deliver a step change in plant
sustainability, productivity, and availability metrics,” says Kevin Prouty, VP Industrials, IDC Corporation. “But
to land this opportunity, companies must be able to deploy data science innovation to front line engineers
with the expertise, data, and plant context to make decisions on insights provided by these new algorithms.”
Examples of customers using Seeq applications to access and integrate data science innovation include an
oil & gas company deploying a deep-learning-based emissions prediction algorithm, a pharmaceutical
company using an unsupervised learning algorithm to proactively detect sensor drift in sensitive batch
processes, and a chemical customer using pattern learning to identify root causes of process instability and
extend cycle time.
“Seeq provides a bridge between data science teams and their algorithms to front-line employees in
hundreds of plants around the world,” says Brian Parsonnet, CTO at Seeq Corporation. “Deploying
algorithms is now as simple as registering them in Seeq, and then defining which employees have access to
them in their Seeq applications.”
Seeq first shipped machine learning features in 2017 in Seeq Workbench, and then in 2020 introduced Seeq
Data Lab for Python scripting and access to any machine learning algorithm. This support for multiple
audiences—with point and click features for process engineers, low code scripting, and a programming
environment for data scientists engaged in feature engineering and data reduction efforts—delivers an endto-
end solution for organizations with all levels of analytics sophistication.
Seeq is available worldwide through a global partner network of system integrators, which provides training
and resale support for Seeq in over 40 countries, in addition to its direct sales organization in North America
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