List of Google Cloud AutoML Customers
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Since 2010, our global team of researchers has been studying Google Cloud AutoML 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 Google Cloud AutoML 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 Google Cloud AutoML for ML and Data Science Platforms include: Chevron Corporation, a United States based Oil, Gas and Chemicals organisation with 45298 employees and revenues of $193.41 billion, Home Depot, a United States based Retail organisation with 470000 employees and revenues of $159.51 billion, Carrefour Spain, a Spain based Retail organisation with 58500 employees and revenues of $14.00 billion, The Daily Telegraph, a United Kingdom based Media organisation with 1047 employees and revenues of $305.0 million, Layer 6, a Canada based Professional Services organisation with 100 employees and revenues of $30.0 million and many others.
Contact us if you need a completed and verified list of companies using Google Cloud AutoML, 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 Google Cloud AutoML 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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California Design Den | Retail | 250 | $25M | United States | Google Cloud AutoML | ML and Data Science Platforms | 2016 | Pluto7 |
In 2016 California Design Den implemented Google Cloud AutoML as the core machine learning component in a Planning In A Box deployment, aligning the retailer with ML and Data Science Platforms capabilities. The implementation was driven by a partnership with Pluto7 and the vendor solution Planning In A Box, both delivered on Google Cloud Platform to apply machine learning and artificial intelligence to demand prediction and supply balancing.
The deployment centered on demand forecasting and supply balancing workflows, with Google Cloud AutoML used for model training, automated model selection, and inference orchestration. Configuration work emphasized time series forecasting and feature engineering pipelines typical of ML and Data Science Platforms, and the Planning In A Box SaaS surface was configured to present forecast outputs to planning users.
Pluto7 led implementation and operationalization, embedding model scoring into merchandising and planning routines and establishing scheduled model retraining and data pipeline cadence. The architecture combined Planning In A Box SaaS orchestration with Google Cloud AutoML model lifecycle management to produce repeatable forecast runs and to feed planning workflows.
Operational scope focused on merchandising and supply chain planning functions within California Design Den, with governance centered on operationalizing forecasts into existing planning cycles and defining ownership for model updates and data quality. The narrative reflects an enterprise SaaS on Google Cloud Platform using Google Cloud AutoML, implemented in 2016 by Pluto7 to support demand prediction and supply balancing at the retailer.
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Carrefour Spain | Retail | 58500 | $14.0B | Spain | Google Cloud AutoML | ML and Data Science Platforms | 2019 | n/a |
In 2019, Carrefour Spain implemented Google Cloud AutoML as its chosen ML and Data Science Platforms capability to accelerate machine learning model development on Google Cloud. Google Cloud AutoML was used to introduce automated model training, feature engineering workflows, model evaluation and managed model serving, aligning platform-level ML functions with the retailer's analytic objectives.
The implementation emphasized model lifecycle automation and reproducible pipelines, with AutoML configured to handle data ingestion, preprocessing, automated hyperparameter selection and deployment into managed inference endpoints. Configuration focused on integration with Google Cloud storage and data processing services to support iterative training and validation, consistent with standard ML and Data Science Platforms operational patterns.
This work occurred alongside broader Google Cloud initiatives that included a SAP HANA production deployment by Carrefour Spain and the use of Google Cloud migration capabilities such as Migrate for Compute Engine. The deployment leveraged Google Cloud’s Cloud Acceleration Program for guidance, migration templates and financial incentives, positioning AutoML implementation within a coordinated cloud adoption program.
Governance practices centered on centralized model promotion controls and alignment with existing cloud migration workflows, incorporating change management and platform-level access controls to manage model provenance and production deployments. The narrative aligned ML operations with enterprise analytics needs and with Google Cloud tooling that had proven effective for SAP customers, who reported reduced staff time for SAP migrations under the same acceleration program.
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Chevron Corporation | Oil, Gas and Chemicals | 45298 | $193.4B | United States | Google Cloud AutoML | ML and Data Science Platforms | 2016 | n/a |
In 2016 Chevron Corporation adopted Google Cloud AutoML as an ML and Data Science Platforms solution to support image analytics and visual search workloads. Google reported that there were 14,000 customers paying to use Google AI services and more than 19,000 customers actively using Google Cloud AutoML, and Chevron Corporation is cited among those users.
Chevron implemented the vision capabilities of Google Cloud AutoML to visually search a massive trove of images stored in thousands of distributed documents, a use case described by research analyst Laura Bandura. The implementation leveraged Cloud AutoML vision model workflows, including automated model training and tuning, inference serving for image classification and similarity search, and the creation of visual indexes to enable queryable image discovery across large unstructured image sets.
The deployment was integrated with Chevron’s distributed document repositories and large image stores to surface visual results across document boundaries, and it was operated by research and analytics teams to support exploratory image analysis. Governance and operational changes focused on image ingestion and labeling pipelines to feed AutoML training, and on controlled access to the visual index for research functions.
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Home Depot | Retail | 470000 | $159.5B | United States | Google Cloud AutoML | ML and Data Science Platforms | 2017 | n/a |
In 2017 Home Depot implemented Google Cloud AutoML as part of a broader move to Google Cloud to embed advanced machine learning into its supply chain. The deployment aligns Home Depot, Google Cloud AutoML, and BigQuery under the ML and Data Science Platforms category to operationalize forecasting and model selection directly against enterprise data.
The implementation emphasizes model development and automated model selection, with analysts using BigQuery ML to run machine learning directly on BigQuery datasets and Google Cloud AutoML to determine the best predictive models. Functional capabilities implemented include demand forecasting, supplier lead time estimation, and estimated delivery time predictions, with AutoML used to evaluate and surface top performing models for production scoring.
Architecturally the solution is built on Google Cloud storage and BigQuery analytics, with engineering teams adapting BigQuery to monitor, analyze, and act on application performance data across stores and warehouses in real time. Operational scope covers supply chain planning, analytics teams, site operations at stores and distribution centers, and engineering responsible for real time performance telemetry and model operationalization.
Governance shifted toward data driven decision workflows, where analytics outputs feed supply chain and replenishment processes to inform buying and logistics. Home Depot reports a more efficient supply chain and improved security posture as explicit outcomes, and the implementation centralized predictive model development within Google Cloud AutoML and BigQuery ML to standardize forecasting and operational analytics.
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Layer 6 | Professional Services | 100 | $30M | Canada | Google Cloud AutoML | ML and Data Science Platforms | 2023 | n/a |
In 2023 Layer 6 deployed Google Cloud AutoML within its ML and Data Science Platforms footprint to support generative AI experiments on tabular data and automated feature search workflows. The deployment was driven by the AI research team and ADP style ML engineering practices documented by an AI Research Engineer working on generative AI in tabular data and feature search using AutoML.
The implementation emphasized AutoML driven feature search, automated model selection and hyperparameter tuning as core capabilities of Google Cloud AutoML. Configuration included pipelines for iterative feature engineering and experiment orchestration, with AutoML used to surface candidate feature sets and baseline models for downstream refinement by researchers.
Integrations were implemented with PySpark data processing pipelines and Azure Databricks for data preparation and orchestration, and PyTorch was used for downstream custom model development and experiments. Operational scope centered on the Layer 6 AI research and ML engineering teams in Toronto, applying the ML and Data Science Platforms to professional services use cases focused on tabular datasets.
Governance and workflow changes focused on embedding AutoML outputs into existing model iteration workflows, introducing standardized experiment handoff from AutoML to custom model development, and formalizing versioned model artifacts and evaluation checkpoints within the research to production pathway. The narrative reflects a configuration-first approach to instrument Google Cloud AutoML for feature search and generative tabular modeling without introducing additional named implementation partners.
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Media | 1047 | $305M | United Kingdom | Google Cloud AutoML | ML and Data Science Platforms | 2018 | n/a |
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Buyer Intent: Companies Evaluating Google Cloud AutoML
ARTW Buyer Intent uncovers actionable customer signals, identifying software buyers actively evaluating Google Cloud AutoML. Gain ongoing access to real-time prospects and uncover hidden opportunities. Companies Actively Evaluating Google Cloud AutoML for ML and Data Science Platforms include:
- Sohu.com Limited, a China based Professional Services organization with 4900 Employees
- Ministry of Communications and Information Technology, a Saudi Arabia based Government company with 1700 Employees
Discover Software Buyers actively Evaluating Enterprise Applications
| Logo | Company | Industry | Employees | Revenue | Country | Evaluated |
|---|---|---|---|---|---|---|
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Sohu.com Limited | Professional Services | 4900 | $836M | China | 2025-12-18 |
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Ministry of Communications and Information Technology | Government | 1700 | $420M | Saudi Arabia | 2025-07-24 |
FAQ - APPS RUN THE WORLD Google Cloud AutoML Coverage
Google Cloud AutoML is a ML and Data Science Platforms solution from Google.
Companies worldwide use Google Cloud AutoML, from small firms to large enterprises across 21+ industries.
Organizations such as Chevron Corporation, Home Depot, Carrefour Spain, The Daily Telegraph and Layer 6 are recorded users of
Google Cloud AutoML for ML and Data Science Platforms.
Companies using Google Cloud AutoML are most concentrated in Oil, Gas and Chemicals, Retail and Media, with adoption spanning over 21 industries.
Companies using Google Cloud AutoML are most concentrated in United States, Spain and United Kingdom, with adoption tracked across 195 countries worldwide. This global distribution highlights the popularity of Google Cloud AutoML across Americas, EMEA, and APAC.
Companies using Google Cloud AutoML range from small businesses with 0-100 employees - 16.67%, to mid-sized firms with 101-1,000 employees - 16.67%, large organizations with 1,001-10,000 employees - 16.67%, and global enterprises with 10,000+ employees - 50%.
Customers of Google Cloud AutoML 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 Google Cloud AutoML 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.