List of ZenML Customers
Since 2010, our global team of researchers has been studying ZenML 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 ZenML for MLOps 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 ZenML for MLOps Platforms include: Groupe Adeo, a France based Professional Services organisation with 150000 employees and revenues of $27.64 billion, JetBrains, a Czech Republic based Professional Services organisation with 1800 employees and revenues of $489.0 million, Brevo, formerly Sendinblue, a France based Professional Services organisation with 850 employees and revenues of $100.0 million and many others.
Contact us if you need a completed and verified list of companies using ZenML, 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 ZenML 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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Brevo, formerly Sendinblue | Professional Services | 850 | $100M | France | ZenML | ZenML | MLOps Platforms | 2024 | n/a |
In 2024, Brevo implemented ZenML as its MLOps Platforms to unify machine learning pipelines across Google Cloud services, including Vertex AI and BigQuery ML, for email marketing and fraud detection workloads in France. The deployment targeted marketing ML teams and centralized pipeline orchestration to standardize development to production flows across the organization.
ZenML was configured to deliver core MLOps capabilities typical of MLOps Platforms, including pipeline orchestration, reproducibility, experiment tracking, and automated model deployment. Configuration emphasized modular pipeline templates for feature engineering, model training, validation, and promotion, enabling consistent CI CD style workflows for small data science teams.
Integrations were explicitly implemented with Vertex AI and BigQuery ML to execute training and serving on Google Cloud, and pipelines were instrumented to transfer artifacts and metadata between experiment tracking and Vertex AI model lifecycle components. Operational coverage remained focused in France, where small data science teams were enabled to own end to end development to production workflows in days, the program put five models into production, and reduced ML deployment time by approximately 80 percent.
Governance was structured around team ownership of pipelines and embedded deployment policies in ZenML pipelines to enforce reproducibility and traceability, aligning pipeline configuration with marketing ML process controls and production promotion gates.
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Groupe Adeo | Professional Services | 150000 | $27.6B | France | ZenML | ZenML | MLOps Platforms | 2024 | n/a |
In 2024, Groupe Adeo implemented ZenML as an MLOps Platforms solution to streamline retail ML/AI workflows across its France operations. The deployment targeted standardization of dev-to-prod machine learning pipelines and improving reproducibility and pipeline portability for retail data-science teams.
ZenML was configured to provide pipeline orchestration, reproducible experiment tracking, artifact and model versioning, and portable pipeline definitions that enable consistent execution from development through production. The implementation introduced automation for pipeline execution and CI/CD oriented workflows for model promotion, aligning with common MLOps Platforms capabilities.
The implementation integrated into existing retail data-science workflows and dev-to-prod toolchains to support collaboration between data scientists and ML engineers. Operational coverage focused on retail ML/AI teams in France, extending across data science and ML engineering functions within Groupe Adeo.
Governance shifted toward standardized pipeline templates, reproducibility controls, and portability policies to reduce environment drift and enforce consistent deployment practices. The move shortened time-to-market from about 8.5 weeks to 2 weeks, and at the time of the case study there were five production models and measurable increases in deployment efficiency.
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JetBrains | Professional Services | 1800 | $489M | Czech Republic | ZenML | ZenML | MLOps Platforms | 2025 | n/a |
In 2025 JetBrains standardized its ML/LLM platform on ZenML to centralize data science and agent evaluation pipelines on Kubernetes. The MLOps Platforms deployment consolidated a previously fragmented Kubeflow and Prefect stack and followed a phased implementation model with a proof of concept and full rollout in 2025 across the Czech Republic and Europe.
ZenML was configured to operate as the central pipeline orchestration and experiment management layer, instrumenting pipeline templates, model evaluation routines, and metadata capture for reproducible workflows. The implementation emphasized pipeline orchestration for agentic evaluation, scalable node scheduling, workflow versioning, and automated artifact handling to support complex, long running pipelines.
Operational coverage centered on JetBrains data science and platform engineering teams, with ZenML running on Kubernetes clusters to manage agentic workloads. The deployment consolidated prior orchestration footprints and enabled ZenML to manage agentic pipelines exceeding 3,000 nodes while operating across JetBrains sites in the Czech Republic and wider European regions.
Governance and rollout processes were formalized during the phased POC and rollout in 2025, establishing centralized pipeline governance, role based access controls, standardized evaluation pipelines, and documentation for reproducible model and agent testing. Active user adoption increased from 8 to 44 and ZenML now functions as the standardized MLOps Platforms layer for JetBrains, improving governance and scalability of ML and LLM evaluation workflows.
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Buyer Intent: Companies Evaluating ZenML
- HM Revenue & Customs, a United Kingdom based Government organization with 67500 Employees
Discover Software Buyers actively Evaluating Enterprise Applications
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