List of Ada Mode Atlas Customers
Bristol, BS1 6BX,
United Kingdom
Since 2010, our global team of researchers has been studying Ada Mode Atlas 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 Ada Mode Atlas for Digital Twin 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 Ada Mode Atlas for Digital Twin include: Electricity of France, a France based Utilities organisation with 171862 employees and revenues of $151.00 billion, EDF Energy, a United Kingdom based Utilities organisation with 11000 employees and revenues of $12.00 billion, Sellafield, a United Kingdom based Oil, Gas and Chemicals organisation with 10890 employees and revenues of $3.23 billion, The Solent Cluster United Kingdom, a United Kingdom based Non Profit organisation with 10 employees and revenues of $1.0 million and many others.
Contact us if you need a completed and verified list of companies using Ada Mode Atlas, 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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EDF Energy | Utilities | 11000 | $12.0B | United Kingdom | Ada Mode | Ada Mode Atlas | Digital Twin | 2023 | n/a |
In 2023, EDF Energy deployed Ada Mode Atlas for the Apps Category . The implementation targeted EDF Energy's United Kingdom nuclear fleet and focused on accelerating chemical clean campaign design by enabling rapid simulation iteration and broader multi objective optimisation using data driven modelling techniques.
The deployment centered on surrogate modelling capabilities and a digital twin enabled optimisation layer delivered by Ada Mode Atlas, configured to substitute computationally expensive simulation runs with trained surrogate models for campaign scenario exploration. Functional modules implemented included surrogate model training and validation, design of experiments orchestration, and optimisation workflows to support multi objective trade off analysis across chemical cleaning parameters.
The project was executed in the United Kingdom and operated against the nuclear fleet operational scope, aligning engineering and chemistry planning functions to a unified modelling environment. Ada Mode Atlas was positioned as the digital twin capability used to ingest operational and campaign input data, drive rapid scenario iteration, and produce optimisation-ready outputs for engineering review.
Governance and rollout emphasized cross functional collaboration between fleet engineering and plant chemistry teams, with configuration and validation cycles to align surrogate models to plant signals and campaign constraints. The work delivered orders of magnitude faster simulation iteration and enabled broader multi objective optimisation capabilities for chemical clean campaign design, as described in Ada Mode case material.
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Electricity of France | Utilities | 171862 | $151.0B | France | Ada Mode | Ada Mode Atlas | Digital Twin | 2017 | n/a |
In 2017, Electricity of France deployed Ada Mode Atlas as a machine health digital twin to support turbine maintenance operations across its generation organization. Ada Mode Atlas was introduced to provide continuous modeling of turbine components and to feed condition-based maintenance decisioning into existing maintenance workflows.
Implementation centered on Ada Mode Atlas core capabilities for machine health modeling, condition monitoring and predictive analytics, with configuration focused on asset health scoring and maintenance prioritization. The deployment used the Ada Mode Atlas application to consolidate equipment-state representations and generate actionable maintenance signals for maintenance planners and asset managers.
Governance positioned Ada Mode Atlas within long-term maintenance strategy and operational decisioning, with the maintenance organization adopting the platform for routine maintenance planning and outage duration reduction. Electricity of France reports that Ada Mode Atlas enabled a significant reduction in turbine maintenance costs and shortened outage duration, and the application is now central to the companys long-term maintenance strategy.
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Sellafield | Oil, Gas and Chemicals | 10890 | $3.2B | United Kingdom | Ada Mode | Ada Mode Atlas | Digital Twin | 2023 | n/a |
In 2023 Sellafield engaged Ada Mode to deploy Ada Mode Atlas for predictive maintenance and intelligent asset management. The engagement was delivered in the United Kingdom as part of Sellafield's AI adoption roadmap and focused on proofs of concept aimed at accelerating nuclear decommissioning, improving plant availability, and reducing operational risk.
Ada Mode Atlas was implemented as a digital twin and AI orchestration layer that modeled key plant assets, ingested telemetry for condition monitoring, and executed anomaly detection and predictive failure models. Functional capabilities implemented in the proofs of concept included asset health scoring, remaining useful life estimation, and prescriptive maintenance guidance to support operational decision making.
The implementation linked sensor network telemetry and plant historian feeds into the Atlas platform and surfaced model outputs into maintenance planning and asset management workflows to inform operations and maintenance teams. Operational coverage emphasized asset management, reliability engineering, and operations functions within Sellafield's nuclear decommissioning program.
Governance for the work was aligned to Sellafield's AI adoption roadmap and followed a staged proofs of concept approach, with collaboration between asset management, engineering, and operations to validate models prior to wider adoption. Outcomes explicitly targeted by the engagement were to accelerate decommissioning activities, improve plant availability, and reduce operational risk.
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Non Profit | 10 | $1M | United Kingdom | Ada Mode | Ada Mode Atlas | Digital Twin | 2024 | n/a |
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