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The Buyer’s Guide to GE Predix

In August 2015, GE announced the launch of the Predix Cloud, the first ever Cloud provided as a PaaS built for industrial data and analytics. GE Predix was designed with the goal of transforming industrial ecosystems by including analytics in the cloud to increase power plan efficiency,reliability and operating savings.

GE acquired two Artificial Intelligence companies to provide capabilities on the Cloud for industrial applications. GE forecasts revenues of $15 billion by 2020, whilst they estimate the industrial internet to be a $225 billion market by 2020. It should be noted that in late 2017 GE took a time out to make changes in Predix.

How is GE’s platform different from Cloud offerings such as the one provided by Amazon? Amazon has built grid computing platform (or Cloud) through an open source system to innovate and maintain their services. However, Predix also provides a “computing and application services in the cloud” for specific industrial use. In addition, more than a PaaS, GE Predix can operate in a distributed industrial architecture, facilitating offline and online communication between systems, and integration with existing ones.

GE is building an extensive partner ecosystem. Partnerships with numerous domain experts add a variety of operational capabilities in diverse industries. It is working with over 270 partners, and 20,000 software developers.

In August 2016, GE announced a partnership with Oracle. Predix will provide a Platform-as-a-Service (PaaS) Cloud dedicated to use machine data for analysis, whilst Oracle will use its Cloud Platform, ERP and supply chain management applications to automate and optimize processes, increase supply chain efficiencies and for predictive maintenance

In addition, GE partnered with Microsoft to integrate its Azure IoT Suite along with business apps such as Office 365 to connect industrial data (handled by Predix Cloud) to business processes and analytics (Business intelligence).

GE Predix versus Siemens MindSphere

The Predix Edge

There are two choices to transfer data from machine to Predix: (1) The manufacturing plant has its own data recording systems (through third party or on their own) that is sent to Predix Cloud or (2) Predix installs a small server directly on the machines to conduct on premise analysis and action.

There is considered an important capability. Transmitting data from systems to the cloud which increases connectivity in remote locations, (e.g., offshore wind farms). With the Edge package, Cloud computing will be closer to the machine itself to enable immediate action to be taken based on real time data analysis of data (e.g. optimizing a train’s energy consumption while running).

Cloud Foundry

The Cloud Foundry system provides a PaaS on top of the Data infrastructure. GE Predix manages databases, security and integration and run times which enables high scalability. The production plant selects analytics devices based on their requirements. If customization is required, then the manufacturing plant may need to build their own devices.

The Digital Twin

The Digital Twin is built on GE Predix. A virtual copy of a production machine’s physical environment is developed and it simulates multiple potential scenarios. GE’s Chief Digital Officer William Ruh explains that through industrial platforms like Predix “we can create a model of a physical machine and from the data we get from that machine, we can have an exact duplicate in the digital world of the machine.”

Deployment: The GE Digital Twin deployment timeline is extensive. A complete and accurate virtual simulation is required based on the blueprints of the underlying asset. Also, the operational environment needs to be re-created and it needs to be trained for various scenarios before it can be used.

The Predix Pricing Model

GE Predix offers a Platform-as-a-Service (PaaS) using“a subscription-based, pay-as-you-go pricing model, allowing customers to easily access and scale services as their business needs evolve”. Industrial customers purchase the analytics tools they need for their business, as well as a suitable subscription plan. There are currently three packages: Professional, Premium and Enterprise packages. Pricing is based on the amount of data collected (number of devices X number of times data is collected by day X 365). Additional fees for various analytical tools are based on requirements.

Predix Pro’s and Con’s

Pro’s Con’s
  • GE has deep expertise in the industrial world.
  • Incumbents such as AWS have a lead start in operating massive public clouds
  • A robust partner ecosystem addresses a wide range of client requirements.
  • Developers lack industry domain expertise, thereby limiting their abilities to develop vertically aligned applications.
  • Pilot-testing and real-time visualization for risk-averse clients.  The ability to test a technology and visualize the risks through simulations accelerates the adoption of new technology.

The Buyer’s Guide to Siemens MindSphere

Siemens announced the launch of MindSphere in July 2016, as an open ecosystem for industrial companies to use as a platform to develop their own applications and analytical services.
Siemens has many partners, which can be divided into three different categories:

  • Competence: partners used for their in-depth product knowledge to tailor solutions specific to certain industries.
  • Performance: partners used for their knowledge of supply chain, development of an optimally developed solution to lower costs and increase efficiency.
  • Investment Protection: consulting, engineering, installation and services.

How it works: Connecting data to the Siemens Cloud:

Siemens MindSphere ensures a very high connectivity. It is using an OPC system to securely connect machines and data originating from industrial plants to the Cloud. OPC has properties that enables an interoperability, thus allowing the connection of third party machines and non-Siemens machines to the Cloud. This interoperability extends to the connection of machines with external systems.

Siemens claims to use latest cyber technology for data protection. In addition, in sharp contrast to GE Predix which claims to own the algorithms generating the data, Siemens is a lot more ambiguous on this topic, and does not make this assertion. Therefore, users can be more assured that their data won’t be used for other purposes. MindSphere provides a large choice in data storage options. Users may choose between a public Cloud, a private Cloud or an “on-site” Cloud solution for clients preferring to use their own infrastructure.

How does MindSphere Digital Twin compare to GE Predix Digital Twin?

Siemens claims to be the only predictive maintenance solution provider to offer the Digital Twin across the whole value chain: products, production and complete plants. This characteristic enables faster market entry of products. By analyzing products data, a firm can gain information on the way products are used by customers.


MindSphere infrastructure uses AWS and SAP HANA as a Cloud platform which allows users to develop, expand and operate applications on the Cloud. Developers can construct their own applications to fit their industry’s requirements.

Siemens launched MindSphere Rocket Club to promote IoT start-ups: start-ups can design industry specific applications to be shared with industry leaders, in exchange for intensive promotion and direct customer interaction through MindSphere. This promotes innovation on their platform, through a mutually beneficial structure for start-ups and large companies.

MindSpherePro’s and Con’s

Pro’s Con’s
  • Siemens is also building professional services offerings to support MindSphere.
  • MindSphere is designed as an open ecosystem. There is an API open to third parties to develop applications.
  • Development of Digital Twin requires access to equipment blueprint and input from plant technicians.
  • Data from machinery from multiple manufacturers can be analyzed within MindSphere.
  • Siemens has thoroughly tested MindSphere in its manufacturing facilities.
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Samuel Attal

Samuel Attal

Samuel-Georges Attal is a marketing intern at Presenso and a third-year student the London School of Economics and Political Science (LSE).