List of SmartSignal Customers
GE Digital
2700 Camino Ramon,
San Ramon, 94583, CA,
United States
San Ramon, 94583, CA,
United States
1 925-242-6200
Professional Services
5900
$958M
Since 2010, our global team of researchers has been studying SmartSignal customers around the world, aggregating massive amounts of data points that form the basis of our forecast assumptions and perhaps the rise and fall of certain vendors and their products on a quarterly basis.
Each quarter our research team identifies companies that have purchased SmartSignal for Asset Performance Management from public (Press Releases, Customer References, Testimonials, Case Studies and Success Stories) and proprietary sources, including the customer size, industry, location, implementation status, partner involvement, LOB Key Stakeholders and related IT decision-makers contact details.
Companies using SmartSignal for Asset Performance Management include: TotalEnergies, a France based Oil, Gas and Chemicals organisation with 100000 employees and revenues of $195.61 billion, Gerdau, a Brazil based Manufacturing organisation with 30000 employees and revenues of $16.82 billion, A2A, a Italy based Utilities organisation with 13267 employees and revenues of $16.80 billion, National Industrialization Co (Tasnee), a Saudi Arabia based Oil, Gas and Chemicals organisation with 3200 employees and revenues of $950.0 million and many others.
Contact us if you need a completed and verified list of companies using SmartSignal, including the breakdown by industry (21 Verticals), Geography (Region, Country, State, City), Company Size (Revenue, Employees, Asset) and related IT Decision Makers, Key Stakeholders, business and technology executives responsible for the software purchases.
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| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Application | Category | When | SI | Insight |
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A2A | Utilities | 13267 | $16.8B | Italy | GE Digital | SmartSignal | Asset Performance Management | 2016 | n/a |
In 2016, A2A implemented GE Vernova's SmartSignal within an Asset Performance Management program for power generation asset monitoring. The deployment targeted combined cycle gas turbines and other plant equipment, and it was operated across multiple Italian sites to detect anomalies and prevent equipment failures.
The SmartSignal implementation focused on predictive analytics and automated anomaly detection, with configuration of asset models and continuous monitoring workflows. Models and monitoring practices have matured since 2016, enabling condition monitoring, asset health scoring, and alerting that support maintenance decisioning and fault escalation processes.
A2A transitioned from a long running on premises monitoring approach to a cloud APM architecture, centralizing model management and monitoring operations while maintaining site level instrumentation for turbine and plant equipment coverage. The implementation supports operational visibility for operations and maintenance teams across the company’s Italian generation sites, and SmartSignal is used as the analytics engine within the Asset Performance Management stack.
Governance centered on model lifecycle management and operationalizing analytics for maintenance workflows, with monitoring and model refinement ongoing since the initial 2016 deployment. The system has delivered early detection of bearing and valve issues and has helped avoid major outages in Italy, supporting A2A’s preventive maintenance and reliability objectives.
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Gerdau | Manufacturing | 30000 | $16.8B | Brazil | GE Digital | SmartSignal | Asset Performance Management | 2016 | n/a |
In 2016, Gerdau implemented GE Digital’s SmartSignal as part of an Asset Performance Management deployment across its Brazilian steel operations. The initial deployment began as a pilot covering 50 critical assets to validate predictive maintenance workflows and to detect incipient equipment failures that cause unplanned downtime.
The implementation combined SmartSignal with a Historian for high frequency data capture and condition monitoring, establishing predictive analytics, anomaly detection, and alerting capabilities. Configuration emphasized model tuning, alarm thresholds, and automated alert routing to maintenance teams to enable condition based interventions and to feed maintenance planning processes.
Following two early detections during the pilot that paid for the initial effort, Gerdau scaled the solution to monitor 600 assets across 11 plants in Brazil. Operational coverage included on-site maintenance crews and centralized maintenance planners, with dashboards and alert streams integrated into plant operations for faster fault identification.
Rollout governance employed phased scaling, validation gates for model acceptance, and centralized oversight for threshold management and alarm suppression. The SmartSignal Asset Performance Management deployment supported broader predictive maintenance adoption at Gerdau and improved maintenance outcomes and asset availability as reported during the pilot and subsequent rollout.
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National Industrialization Co (Tasnee) | Oil, Gas and Chemicals | 3200 | $950M | Saudi Arabia | GE Digital | SmartSignal | Asset Performance Management | 2024 | n/a |
In 2024, National Industrialization Co (Tasnee) integrated SmartSignal into its Asset Performance Management program through GE Vernova. TASNEE will be the first petrochemical company in the Gulf region to use predictive analytics within its APM workflows.
SmartSignal is implemented as a predictive analytics layer to detect, diagnose, forecast and help prevent emerging equipment failures, leveraging machine learning models and analytics to shift monitoring from reactive inspection to proactive condition based maintenance. GE Vernova's APM suite, including its Reliability application, is used as the orchestration plane for SmartSignal alerts and model outputs, creating a composable Asset Performance Management architecture.
The implementation covers TASNEE's extensive petrochemical operations in Saudi Arabia and centers on reliability and maintenance functions, where SmartSignal outputs feed maintenance planning and operations workstreams. Integration is explicitly into TASNEE's existing APM workflows and into GE Vernova's Reliability application, aligning predictive insights with asset health dashboards and maintenance scheduling processes.
Governance and workflow changes were scoped to embed predictive analytics into APM governance, with reliability teams operationalizing SmartSignal outputs in maintenance decision making and scheduling. The stated goals are to enhance operational efficiency, reliability, and sustainability, and to optimize maintenance schedules and minimize unplanned downtime.
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TotalEnergies | Oil, Gas and Chemicals | 100000 | $195.6B | France | GE Digital | SmartSignal | Asset Performance Management | 2013 | n/a |
In 2013, TotalEnergies implemented GE Digital's Proficy SmartSignal predictive analytics solution, SmartSignal, as part of its Asset Performance Management capabilities. The deployment positioned SmartSignal to support reliability and maintenance use cases for rotating turbo machinery across the company.
The implementation emphasized remote monitoring and condition based monitoring of a large fleet of rotating turbo machinery, using predictive analytics and anomaly detection to generate early warnings and prioritized diagnostics. SmartSignal's monitoring and analysis suite was configured for fleet level diagnostics and alarm prioritization, aligning with Asset Performance Management workflows such as predictive maintenance orchestration and asset health monitoring. These functional capabilities enabled centralized identification of asset degradation patterns and diagnostic prioritization for maintenance planning.
The program was executed as a multi year fleet deployment announced mid 2013, with operational scope covering TotalEnergies global oil and gas production sites. The deployment centralized analytics for distributed assets and routed diagnostics to reliability engineering, operations and maintenance teams to support coordinated response across sites. Rollout emphasis was on standardized diagnostic logic and fleet scale monitoring to create consistent decision inputs for field and central teams.
Governance followed a programmatic rollout model prioritizing fleet diagnostics and standardized alarm logic to support maintenance and reliability organizations. Outcomes stated at announcement included improved reliability, reduced maintenance costs and lower unplanned production losses across TotalEnergies global sites. SmartSignal served as the predictive analytics component within TotalEnergies Asset Performance Management practice.
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| Logo | Company | Industry | Employees | Revenue | Country | Evaluated | ||
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FAQ - APPS RUN THE WORLD SmartSignal Coverage
SmartSignal is a Asset Performance Management solution from GE Digital.
Companies worldwide use SmartSignal, from small firms to large enterprises across 21+ industries.
Organizations such as TotalEnergies, Gerdau, A2A and National Industrialization Co (Tasnee) are recorded users of
SmartSignal for Asset Performance Management.
Companies using SmartSignal are most concentrated in Oil, Gas and Chemicals, Manufacturing and Utilities, with adoption spanning over 21 industries.
Companies using SmartSignal are most concentrated in France, Brazil and Italy, with adoption tracked across 195 countries worldwide. This global distribution highlights the popularity of SmartSignal across Americas, EMEA, and APAC.
Companies using SmartSignal range from small businesses with 0-100 employees - 0%, to mid-sized firms with 101-1,000 employees - 0%, large organizations with 1,001-10,000 employees - 25%, and global enterprises with 10,000+ employees - 75%.
Customers of SmartSignal include firms across all revenue levels — from $0-100M, to $101M-$1B, $1B-$10B, and $10B+ global corporations.
Contact APPS RUN THE WORLD to access the full verified SmartSignal customer database with detailed Firmographics such as industry, geography, revenue, and employee breakdowns as well as key decision makers in charge of Asset Performance Management.