List of C3 AI Reliability Customers
C3 AI
1400 Seaport Boulevard,
Redwood City, 94063, CA,
United States
Redwood City, 94063, CA,
United States
1 650-503-2200
Professional Services
1181
$389M
Since 2010, our global team of researchers has been studying C3 AI Reliability 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 C3 AI Reliability 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 C3 AI Reliability for Asset Performance Management include: Shell, a United Kingdom based Oil, Gas and Chemicals organisation with 96000 employees and revenues of $284.31 billion, Koch Industries, a United States based Oil, Gas and Chemicals organisation with 120000 employees and revenues of $125.00 billion, ENEL, a Italy based Utilities organisation with 61192 employees and revenues of $92.70 billion, Eversource Energy, a United States based Utilities organisation with 10680 employees and revenues of $11.90 billion, Yokogawa Electric, a Japan based Professional Services organisation with 17670 employees and revenues of $4.01 billion and many others.
Contact us if you need a completed and verified list of companies using C3 AI Reliability, 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.
The C3 AI Reliability customer wins are being incorporated in our Enterprise Applications Buyer Insight and Technographics Customer Database which has over 100 data fields that detail company usage of software systems and their digital transformation initiatives. Apps Run The World wants to become your No. 1 technographic data source!
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| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Application | Category | When | SI | Insight |
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ENEL | Utilities | 61192 | $92.7B | Italy | C3.ai | C3 AI Reliability | Asset Performance Management | 2019 | n/a |
In 2019, ENEL deployed C3 AI Reliability as a cornerstone Asset Performance Management implementation within its enterprise-wide digitalization strategy. This deployment was part of a large-scale C3 AI Suite rollout intended to increase efficiency, support new services, and spread a digital culture across the company, and it targeted operational reliability across distribution networks.
C3 AI Reliability was configured to deliver predictive feeder failure capabilities and a time-based as-operated network state, using an advanced in-memory graph network and a continuous learning machine learning framework. The implementation emphasized predictive maintenance workflows for distribution assets, real-time analytics on network sensor streams, and model-driven prioritization of potential faults.
The application integrates heterogeneous operational data, consolidating inputs from SCADA, Grid Topology, Weather, Power Quality, Maintenance, Workforce, Work Management, and Inventory systems. It consumes real-time network sensor data, smart meter telemetry, asset maintenance records, and weather feeds to present a holistic operational view, and the broader C3 AI Suite environment at ENEL runs on a unified, federated cloud image hosted on Amazon Web Services with large-scale graph assets and extensive data ingestion.
Operational coverage included deployment across five control centers and alignment with network operations, maintenance, and workforce management processes to surface actionable alerts and support dispatch decisions. Governance relied on model governance and continuous learning pipelines to refresh prediction performance and to translate AI outputs into operational workflows.
The explicit objective of the C3 AI Reliability deployment was to improve grid reliability and reduce the occurrence of faults, delivering relevant, actionable insights into distribution asset health and failure risk while leveraging the C3 AI Reliability application within ENEL’s Asset Performance Management practice.
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Eversource Energy | Utilities | 10680 | $11.9B | United States | C3.ai | C3 AI Reliability | Asset Performance Management | 2017 | n/a |
In 2017, Eversource Energy deployed C3 AI Reliability as an Asset Performance Management application to centralize analytics for utility asset health and reliability. Eversource used C3 AI Reliability and the C3 AI Platform to connect disparate data sets and draw operational insights, a capability highlighted by Amy Findlay who noted the platform enables promoting the best programs with the right customer.
The implementation focused on Asset Performance Management capabilities such as predictive maintenance modeling, anomaly detection, condition-based monitoring, and asset health scoring, using C3 AI Reliability to run large-scale machine learning models against time series and event data. The deployment emphasized configurable model pipelines and operational dashboards to surface risk and remaining useful life indicators for critical grid and distribution assets.
Operational integrations concentrated on ingesting and harmonizing diverse utility data sources, including sensor and telemetry feeds, SCADA style operational telemetry, GIS and spatial asset records, and work order and maintenance histories, enabling cross-system correlation and prescriptive maintenance planning. The scope targeted core business functions of asset management, field operations, maintenance planning, and reliability engineering across Eversource network operations.
Governance and process changes centered on data consolidation and insight-driven program prioritization, with business stakeholders leveraging C3 AI Reliability outputs to refine program targeting and maintenance workflows. The deployment narrative emphasizes orchestration of disparate data for analytical reliability use cases rather than specific outcome metrics.
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Koch Industries | Oil, Gas and Chemicals | 120000 | $125.0B | United States | C3.ai | C3 AI Reliability | Asset Performance Management | 2017 | n/a |
In 2017, Koch Industries implemented C3 AI Reliability as an Asset Performance Management deployment across its industrial operations. The C3 AI Reliability implementation positioned the application as an enterprise AI platform for asset health analytics and prognostics, reflecting Koch leadership commentary that the technology provided a platform to drive enterprise AI.
The deployment focused on core Asset Performance Management capabilities including predictive maintenance, anomaly detection, time series asset health modeling, and AI-driven failure prognostics. C3 AI Reliability was configured to ingest operational telemetry and industrial signals, apply machine learning models for condition-based monitoring, and surface prioritized alerts and diagnostics for maintenance planners.
Operational coverage emphasized industrial business functions responsible for equipment reliability and maintenance planning, with the system designed to centralize asset analytics across Koch’s operating units. Governance and workflows were adjusted to operationalize machine learning outputs into maintenance decisioning, establishing model validation and repeatable processes for AI model updates and version control.
Jim Hannan, EVP, CEO Enterprises, said, “There’s no question that C3 AI has capabilities we haven’t seen before, with something that gives us a platform to drive enterprise AI.” The narrative underscores Koch Industries C3 AI Reliability implementation as a platform-centric Asset Performance Management effort to embed predictive analytics into asset operations.
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Shell | Oil, Gas and Chemicals | 96000 | $284.3B | United Kingdom | C3.ai | C3 AI Reliability | Asset Performance Management | 2017 | n/a |
In 2017, Shell deployed C3 AI Reliability as an Asset Performance Management application. The initiative was positioned to integrate large volumes of data at scale in the cloud and to operationalize predictive analytics for asset health across operational teams.
The C3 AI Reliability implementation concentrated on scalable data ingestion, feature engineering, and model training pipelines, enabling thousands of machine learning models to be trained and managed in production as described by Dan Jeavons, GM Data Science. Functional capabilities implemented align with Asset Performance Management practices and included predictive maintenance modeling, anomaly detection, asset health scoring, and production model orchestration.
Deployment architecture emphasized cloud scale analytics and integration of telemetry from sensors and operational historians, structured asset registries, and maintenance work order streams into the C3 AI Reliability environment. The operational scope focused on Shell asset and operations teams responsible for equipment reliability and maintenance planning.
Governance and operationalization addressed machine learning lifecycle management, including scheduled retraining, production monitoring of models, and embedding model outputs into maintenance decision workflows. Dan Jeavons characterized the C3 AI platform as a real enabler, enabling Shell to integrate large volumes of data and to operate thousands of machine learning models in production, without specific outcome metrics provided.
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United States Department of Defense | Government | 1000 | $250M | United States | C3.ai | C3 AI Reliability | Asset Performance Management | 2019 | n/a |
In 2019, the United States Department of Defense deployed C3 AI Reliability, an Asset Performance Management application, to predict subsystem failures across multiple aircraft platforms. The implementation targeted predictive maintenance and reliability engineering use cases, configuring C3 AI Reliability to run both model training and ongoing inference against historical and operational platform data.
Functional modules implemented include condition monitoring, anomaly detection, prognostics, and model lifecycle management. The configuration emphasized data ingestion pipelines for sensor and telemetry streams, feature engineering workflows, and recurring inference pipelines to surface time to failure estimates and confidence scores, with explainability tooling to aid diagnostic workflows.
Operational coverage extended across multiple aircraft platforms and supported maintenance, mission operations, and reliability engineering teams within the defense organization. Governance and operational controls were instituted for model validation, version management, threshold tuning, and access control to inference outputs, and rollout was staged by platform to validate predictions and refine model parameters prior to broader operational use.
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Professional Services | 17670 | $4.0B | Japan | C3.ai | C3 AI Reliability | Asset Performance Management | 2018 | n/a |
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Buyer Intent: Companies Evaluating C3 AI Reliability
ARTW Buyer Intent uncovers actionable customer signals, identifying software buyers actively evaluating C3 AI Reliability. Gain ongoing access to real-time prospects and uncover hidden opportunities. Companies Actively Evaluating C3 AI Reliability for Asset Performance Management include:
- Asha Sweet Center, a India based Consumer Packaged Goods organization with 700 Employees
Discover Software Buyers actively Evaluating Enterprise Applications
| Logo | Company | Industry | Employees | Revenue | Country | Evaluated | ||
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FAQ - APPS RUN THE WORLD C3 AI Reliability Coverage
C3 AI Reliability is a Asset Performance Management solution from C3.ai.
Companies worldwide use C3 AI Reliability, from small firms to large enterprises across 21+ industries.
Organizations such as Shell, Koch Industries, ENEL, Eversource Energy and Yokogawa Electric are recorded users of
C3 AI Reliability for Asset Performance Management.
Companies using C3 AI Reliability are most concentrated in Oil, Gas and Chemicals, Utilities and Professional Services, with adoption spanning over 21 industries.
Companies using C3 AI Reliability are most concentrated in United Kingdom, United States and Italy, with adoption tracked across 195 countries worldwide. This global distribution highlights the popularity of C3 AI Reliability across Americas, EMEA, and APAC.
Companies using C3 AI Reliability range from small businesses with 0-100 employees - 0%, to mid-sized firms with 101-1,000 employees - 16.67%, large organizations with 1,001-10,000 employees - 0%, and global enterprises with 10,000+ employees - 83.33%.
Customers of C3 AI Reliability 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 C3 AI Reliability 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.