Mtell Partners with OSIsoft to Enable Asset Prescriptive Maintenance

By | October 30th, 2015|Mtell Previse, News, Oil and Gas, Partners|

New partnership integrates Mtell’s Machine Learning Technology with the OSIsoft’s PI System to Optimize Asset Health for Industrial Enterprises

SAN DIEGO (OCTOBER 29, 2015) – Mtell, a leading asset health software solution company and provider of machine learning technology for the Industrial Internet of Things (IIoT), today announced it has partnered […]

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Fixing Problems Before They Arise in Oil and Gas

By | August 1st, 2015|Big Data, Conference, Industrial Internet of Things, Machine Learning, Mtell Reservoir, Oil and Gas, Partners|

Originally posted by Arunima Kumar in SAP Business Trends on Jul 20, 2015

As part of its IoT kickstarter program, the SAP Co-innovation Lab in Silicon Valley partnered with Mtell and Rolta on a solution for predictive machine maintenance in oil and gas. Built on SAP HANA, the solution […]

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Mtell’s CTO Presents at SAP’s HANA4IoT Unplugged

By | May 12th, 2015|Big Data, Events, Industrial Internet of Things, Mtell Previse, News, Oil and Gas|

Last month Mtell’s CTO, Alex Bates, presented a comprehensive software demo at SAP’sHANA4IoT Unplugged in Palo Alto, CA. The event took place April 9th, 2015, and featured guest speakers, demos, and an evening networking event. Cisco sponsored the event, bringing in hundreds of global attendees that aim to […]

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Mtell and ThingWorx Partner to Offer Complete Analytics Solution for Internet of Things Applications

By | January 28th, 2015|Industrial Internet of Things, Machine Learning, News, Oil and Gas, Predictive Analytics, Press Release|

Companies will Integrate Mtell’s Machine Learning Technology with the ThingWorx® Platform to Enable Advanced Predictive Analytics for Internet of Things Solutions

SAN DIEGO (January 28, 2014) – Mtell, a leading asset health software solution company and provider of machine learning technology for the Internet of Things (IoT), today […]

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Why Does Machine Learning Lead the CBM Pack?

By | September 26th, 2013|Condition Monitoring, Machine Learning, Oil and Gas|

Mtell condition-monitoring has proved to be superior to other technologies for early detection of machine malfunction, minimization of repair costs, and superior uptime; but why?

There are three fundamental reasons: first the solution is self-learning, second it inherently recognizes the precise patterns of a failure, and third it constantly adapts in […]

How is Mtell Able to Transfer Learned Behaviors from One Machine to Another, While Some Claim all Machines are Unique?

By | September 4th, 2013|Machine Learning, Oil and Gas, Smart Machines|

Many potential customers begin Mtell engagements heavily skeptical about our claim of Transfer Learning capabilities. It’s true that older technology approaches must treat every machine as unique, but Mtell has pioneered modern techniques that contradict such deep-seated wisdom.

Machine Learning techniques are data-driven; using only pure data to learn baseline normal […]