List of SAP Leonardo Machine Learning Customers
SAP
Dietmar-Hopp-Allee 16,
Walldorf, 69190,
Germany
Walldorf, 69190,
Germany
49 6 2277-47474
Professional Services
110650
$42.3B
Since 2010, our global team of researchers has been studying SAP Leonardo Machine Learning 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 SAP Leonardo Machine Learning for ML and Data Science Platforms 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 SAP Leonardo Machine Learning for ML and Data Science Platforms include: Costco, a United States based Retail organisation with 333000 employees and revenues of $254.45 billion, Mercedes Benz, a Germany based Automotive organisation with 175264 employees and revenues of $171.47 billion, BASF, a Germany based Life Sciences organisation with 111408 employees and revenues of $75.74 billion, Cisco Systems, a United States based Professional Services organisation with 86200 employees and revenues of $61.50 billion, Jabil, a United States based Manufacturing organisation with 250000 employees and revenues of $33.48 billion and many others.
Contact us if you need a completed and verified list of companies using SAP Leonardo Machine Learning, 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 Machine Learning software purchases.
The SAP Leonardo Machine Learning 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 Machine Learning 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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Aegea | Professional Services | 4977 | $445M | Brazil | SAP | SAP Leonardo Machine Learning | ML and Data Science Platforms | 2017 | n/a |
In 2017, Aegea engaged the SAP Leonardo Lab in Brazil and deployed SAP Leonardo Machine Learning as a fast track prototyping effort for its Prolagos water distribution business. Aegea SAP Leonardo Machine Learning ML and Data Science Platforms deployment centered on rapid experimentation with IoT ingest, Big Data analytics, and machine learning driven predictive analytics to inform operational decisions in the sanitation and water distribution domain.
The implementation used SAP Leonardo Platform capabilities to prototype machine learning models and predictive analytics workflows, and to author Leonardo Apps that surface analytics into operational processes. Functional modules explored included time series analytics for sensor data, model training and scoring pipelines, and analytics visualization tied to business process contexts. SAP Leonardo Machine Learning was used to contextualize operational data rather than as a standalone reporting layer.
Integrations were explicitly focused on ingesting Big Data from operational technology systems, geographical information systems, and IoT sensors, with the SAP Leonardo Foundation providing the technical services and platform tooling. The deployment pattern emphasized lab-driven prototypes hosted through the SAP Leonardo Lab, enabling data collection from OT and GIS sources and iterative model refinement within the Leonardo environment.
Governance and rollout followed a lab to pilot approach managed by the SAP Leonardo Lab and Aegea teams, with prototypes presented externally at Leonardo Live as part of regional innovation activities. The project scope was prototyping and app building for Prolagos in Brazil, intended to support existing process models or enable new operational workflows through Leonardo Apps and embedded analytics.
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AMAG | Automotive | 6500 | $4.6B | Switzerland | SAP | SAP Leonardo Machine Learning | ML and Data Science Platforms | 2017 | n/a |
In 2017, AMAG implemented SAP Leonardo Machine Learning to support Connected Fleet use cases, presenting the work at SAP Forum Basel 2017. AMAG presented to customers and partners, demonstrating the business value of Connected Fleet from the SAP Leonardo portfolio while framing SAP Leonardo Machine Learning as the ML and Data Science Platforms component for fleet analytics.
The implementation centered on SAP Leonardo Machine Learning capabilities aligned to connected fleet scenarios, including model training and deployment workflows, feature engineering pipelines, and operational analytics for fleet operations. Functional modules emphasized real time scoring, anomaly detection, and predictive analytics patterns common to ML and Data Science Platforms, with model lifecycle management and orchestration embedded in the Leonardo portfolio.
Operational scope targeted AMAGs fleet services and connected vehicle initiatives in Switzerland, embedding machine learning outputs into service planning and connected fleet decision processes. Governance focused on data pipeline standardization and model validation workflows to support repeatable deployments, and AMAG used the SAP Forum Basel demonstration to prove the business value of the Connected Fleet use case while positioning SAP Leonardo Machine Learning within its ML and Data Science Platforms strategy for fleet operations.
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Arctic Wind | Professional Services | 20 | $12M | Norway | SAP | SAP Leonardo Machine Learning | ML and Data Science Platforms | 2017 | n/a |
In 2017, Arctic Wind implemented SAP Leonardo Machine Learning as a maintenance helper. Arctic Wind deployed SAP Leonardo Machine Learning within its ML and Data Science Platforms footprint to support maintenance workflows, tying the company, SAP Leonardo Machine Learning, the ML and Data Science Platforms category, and the maintenance business function together in a single implementation narrative.
For a 20-employee professional services firm, the implementation emphasized lightweight model training and inference pipelines and the use of classification and anomaly detection workflows typical of ML and Data Science Platforms. Configuration focused on embedding model outputs into maintenance decision processes and operational workflows, with governance activity centered on model lifecycle management, retraining cadence, and monitoring to sustain the maintenance helper capability across operations and service delivery teams.
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BASF | Life Sciences | 111408 | $75.7B | Germany | SAP | SAP Leonardo Machine Learning | ML and Data Science Platforms | 2017 | n/a |
In 2017, BASF implemented SAP Leonardo Machine Learning to improve the efficiency of its customer service processes. The SAP Leonardo Machine Learning deployment centers on an AI virtual colleague called CuRT that automates classification and routing of incoming emails and customer request tickets.
The implementation uses core ML capabilities common to ML and Data Science Platforms to automatically categorize inquiries by type, industry, and application, and to assign routing decisions to the appropriate colleague. CuRT operates as a virtual customer service rep that extracts semantic signals from each request, applies model inferences to classify the ticket, and attaches routing metadata to the case record.
Operational coverage is focused on BASF customer service workflows, where automated handling of incoming emails reduces manual triage. Human customer service professionals provide feedback on CuRT assessments, creating a governance loop that continuously retrains and refines the machine learning models, and embeds reviewer input into the operational process.
BASF achieved an important milestone by automating incoming emails and delivering a higher level of service to customers through SAP Leonardo Machine Learning. The relationship between BASF, SAP Leonardo Machine Learning, ML and Data Science Platforms, and the customer service business function is explicit, with ongoing model governance and human-in-the-loop feedback driving continuous improvement.
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Britehouse, a Dimension Data company | Professional Services | 1400 | $200M | South Africa | SAP | SAP Leonardo Machine Learning | ML and Data Science Platforms | 2018 | n/a |
In 2018, Britehouse, a Dimension Data company, deployed SAP Leonardo Machine Learning as a core capability to enter agriculture use cases, positioning the SAP Leonardo Machine Learning implementation within the ML and Data Science Platforms category. The deployment is described as part of a broader initiative to create intelligent enterprises through IoT and machine learning solutions, and it explicitly references integration with SAP Vehicle Insights and Intel technology in customer roadmaps.
The implementation centers on machine learning workflows typical of ML and Data Science Platforms, including IoT data ingestion from vehicle and equipment sensors, telemetry processing, model training and inference pipelines, and predictive scheduling for harvest vehicles. Functional capabilities implemented or planned include vehicle telemetry analytics using SAP Vehicle Insights, crop and factory process modeling, and automated scheduling logic to coordinate field operations and factory inputs.
Integrations cited in the roadmap include SAP Vehicle Insights for asset telemetry and Intel hardware and platform technologies for edge and compute support, enabling end to end data flow from sensors to cloud based machine learning services. Operational scope targets agriculture customers and spans field operations, equipment fleets, crop management, and factory processes, with Britehouse leveraging these components to extend Dimension Data offerings into a new industry segment in South Africa.
Governance and rollout are described as long term roadmaps for customers leveraging SAP Leonardo and Intel, implying staged adoption across customer operations and alignment of data governance to manage IoT and ML data. The narrative emphasizes creating intelligent enterprises, with the stated aim that these SAP Leonardo Machine Learning solutions will efficiently manage harvest vehicle scheduling, crops, and factories through combined IoT and machine learning capabilities.
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Utilities | 22147 | $26.8B | United Kingdom | SAP | SAP Leonardo Machine Learning | ML and Data Science Platforms | 2017 | n/a |
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Utilities | 39000 | $5.7B | China | SAP | SAP Leonardo Machine Learning | ML and Data Science Platforms | 2017 | n/a |
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Professional Services | 86200 | $61.5B | United States | SAP | SAP Leonardo Machine Learning | ML and Data Science Platforms | 2017 | n/a |
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Retail | 333000 | $254.5B | United States | SAP | SAP Leonardo Machine Learning | ML and Data Science Platforms | 2018 | n/a |
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Automotive | 20000 | $7.3B | South Korea | SAP | SAP Leonardo Machine Learning | ML and Data Science Platforms | 2018 | n/a |
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Showing 1 to 10 of 19 entries
Buyer Intent: Companies Evaluating SAP Leonardo Machine Learning
ARTW Buyer Intent uncovers actionable customer signals, identifying software buyers actively evaluating SAP Leonardo Machine Learning. Gain ongoing access to real-time prospects and uncover hidden opportunities. Companies Actively Evaluating SAP Leonardo Machine Learning for ML and Data Science Platforms include:
- Naver, a South Korea based Communications organization with 14000 Employees
Discover Software Buyers actively Evaluating Enterprise Applications
| Logo | Company | Industry | Employees | Revenue | Country | Evaluated | ||
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FAQ - APPS RUN THE WORLD SAP Leonardo Machine Learning Coverage
SAP Leonardo Machine Learning is a ML and Data Science Platforms solution from SAP.
Companies worldwide use SAP Leonardo Machine Learning, from small firms to large enterprises across 21+ industries.
Organizations such as Costco, Mercedes Benz, BASF, Cisco Systems and Jabil are recorded users of
SAP Leonardo Machine Learning for ML and Data Science Platforms.
Companies using SAP Leonardo Machine Learning are most concentrated in Retail, Automotive and Life Sciences, with adoption spanning over 21 industries.
Companies using SAP Leonardo Machine Learning are most concentrated in United States and Germany, with adoption tracked across 195 countries worldwide. This global distribution highlights the popularity of SAP Leonardo Machine Learning across Americas, EMEA, and APAC.
Companies using SAP Leonardo Machine Learning range from small businesses with 0-100 employees - 21.05%, to mid-sized firms with 101-1,000 employees - 5.26%, large organizations with 1,001-10,000 employees - 15.79%, and global enterprises with 10,000+ employees - 57.89%.
Customers of SAP Leonardo Machine Learning 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 SAP Leonardo Machine Learning customer database with detailed Firmographics such as industry, geography, revenue, and employee breakdowns as well as key decision makers in charge of ML and Data Science Platforms.