01ML BUYERS
ML buyers are not general tech contacts. They work on data science, AI products, model training, deploy pipelines, cloud setup, model rules, data quality and MLOps.
MACHINE LEARNING DATABASE
AI & ANALYTICS · TECHNOLOGY USERS EMAIL LIST
Machine Learning Users Email List: Verified Contacts for Google Vertex AI & Amazon SageMaker
Identify companies using TensorFlow, AWS SageMaker, Azure Machine Learning, Hugging Face, MLflow, H2O.ai and other ML platforms for AI model development, MLOps, training and deployment workflows.
Get a free sample of verified machine learning software contacts for AI software sales, MLOps campaigns, ABM and market research.
- 313k+Verified Contacts
- 95%Accuracy Rate
- 60+Countries
- 45 daysRefresh Cycle
Build the segment first, then give us the email
Build your free technology sample. Add a filter or two.
YOUR SEGMENTtechnology contacts
COMPANYLOCATIONSTACK
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THERE IS NO PUBLIC TECHNOLOGY SAMPLE · NAMES, CONTACTS AND YOUR FILTERED COUNT COME WITH THE FREE SAMPLE
WHAT IT IS
Every MLOps record. Fully enriched.
Each record is set up for sales, marketing, CRM and ABM work. It also suits AI consulting outreach and market research.
WHY MACHINE LEARNING PLATFORM DATA MATTERS
02TENSORFLOW
TensorFlow users often focus on deep learning, image and text models, or ML in production. That calls for a very different pitch from a general IT campaign.
03CLOUD ML
SageMaker users build and run models on AWS. Azure Machine Learning users run ML on Microsoft, often with AutoML and strict rules.
04AI STACK
Hugging Face users work with open models, text AI and generative AI. MLflow users track experiments and manage models. H2O.ai users focus on AutoML and forecasts.
05OUTREACH FIT
Know the platform, and your message can fit the buyer. You can speak to their ML stack, cloud, how they build models, their AI maturity, rules, data gaps or MLOps plans.
Request a free sampleNO CARD · NO OBLIGATION · 45-DAY FRESHNESS CYCLE
WHAT YOU GET
Every MLOps record. Fully enriched.
3GROUPS
/34ITEMS
CUT BY FIELDS ON EVERY RECORD
Fields on every record
- Contact Name
- ML Job Title & Seniority
- Verified Business Email
- Phone
- Company Name & Website
- LinkedIn Profile URL
- Industry & Business Sector
- Revenue & Employee Size
- City, State, Country & Region
- ML Platform In Use
- ML Category & MLOps Workflow
CUT BY PLATFORMS COVERED
Platforms covered
- Google Vertex AI
- Amazon SageMaker
- Microsoft Azure Machine Learning
- Databricks ML + Lakehouse
- IBM Watsonx.ai
- SAS Viya
- DataRobot
- Dataiku
- H2O.ai
- Alteryx Machine Learning
- Altair RapidMiner
- KNIME
- Domino Data Lab
- Anaconda Enterprise
- MATLAB MathWorks
CUT BY BUILT FOR AI GROWTH TEAMS
Built for AI growth teams
- AI software vendors targeting ML platform users
- MLOps and model monitoring providers
- Cloud consultants targeting SageMaker and Azure ML users
- Data engineering firms supporting ML pipelines
- AI governance, model risk and security vendors
- Developer tool and DevOps vendors for ML teams
- ABM teams segmenting by ML platform and cloud provider
- Demand generation teams targeting ML-led organisations
Fields on every record11
- Contact Name
- ML Job Title & Seniority
- Verified Business Email
- Phone
- Company Name & Website
- LinkedIn Profile URL
- Industry & Business Sector
- Revenue & Employee Size
- City, State, Country & Region
- ML Platform In Use
- ML Category & MLOps Workflow
Platforms covered15
- Google Vertex AI
- Amazon SageMaker
- Microsoft Azure Machine Learning
- Databricks ML + Lakehouse
- IBM Watsonx.ai
- SAS Viya
- DataRobot
- Dataiku
- H2O.ai
- Alteryx Machine Learning
- Altair RapidMiner
- KNIME
- Domino Data Lab
- Anaconda Enterprise
- MATLAB MathWorks
Built for AI growth teams8
- AI software vendors targeting ML platform users
- MLOps and model monitoring providers
- Cloud consultants targeting SageMaker and Azure ML users
- Data engineering firms supporting ML pipelines
- AI governance, model risk and security vendors
- Developer tool and DevOps vendors for ML teams
- ABM teams segmenting by ML platform and cloud provider
- Demand generation teams targeting ML-led organisations
FIG. 1 The ways a technology user record can be segmented, as described on this page. Name the cut you need and a data specialist builds it into your free sample.
MACHINE LEARNING DATA COVERED
15+ machine learning platforms. One database.
Filter by machine learning platform, AI development tool, region or company size and pull a clean list in minutes.
| Platform | List | Contacts | Companies | Coverage |
|---|---|---|---|---|
| Google Vertex AI | Google Vertex AI Users Email List | 11.3k | 2.3k | Global |
| Amazon SageMaker | Amazon SageMaker Users Email List | 43.7k | 8.7k | Global |
| Microsoft Azure Machine Learning | Microsoft Azure Machine Learning Users Email List | 30k | 6k | Global |
| Databricks ML + Lakehouse | Databricks ML + Lakehouse Users Email List | 97.4k | 19.5k | Global |
| IBM Watsonx.ai | IBM Watsonx.ai Users Email List | 1.6k | 311 | Global |
| SAS Viya | SAS Viya Users Email List | 5.4k | 1.1k | Global |
| DataRobot | DataRobot Users Email List | 3k | 592 | Global |
| Dataiku | Dataiku Users Email List | 6k | 1.2k | Global |
| H2O.ai | H2O.ai Users Email List | 2.5k | 509 | Global |
| Alteryx Machine Learning | Alteryx Machine Learning Users Email List | 1.3k | 265 | Global |
| Altair RapidMiner | Altair RapidMiner Users Email List | 1.6k | 329 | Global |
| KNIME | KNIME Users Email List | 7.7k | 1.5k | Global |
| Domino Data Lab | Domino Data Lab Users Email List | 535 | 107 | Global |
| Anaconda Enterprise | Anaconda Enterprise Users Email List | 3.6k | 728 | Global |
| MATLAB MathWorks | MATLAB MathWorks Users Email List | 97.5k | 19.5k | Global |
Request a free sampleNO CARD · NO OBLIGATION · 45-DAY FRESHNESS CYCLE
HOW IT WORKS
How to build your Machine Learning list
Find companies by the ML platform they run. Then narrow by MLOps task, cloud, AI maturity, industry, region and role.
Select ML platforms and workflows
Pick the ML platforms you want to reach. Choose TensorFlow, AWS SageMaker, Azure Machine Learning, Hugging Face, MLflow, H2O.ai, Kubeflow or Databricks Mosaic AI. Then pick the work, such as training, deployment or MLOps.
Define buyer roles and filters
Pick the people who buy. Most teams choose ML, MLOps and AI engineers, data scientists, the CDO, CTO, VP Engineering or AI product leads. Then narrow by industry, size and cloud.
Launch targeted AI outreach
Use the list for cold email, calls, LinkedIn, ABM, partner outreach, CRM updates or research. Each contact runs the ML tools your offer is built for.
- Verified ML platform contacts
- ML engineers email list B2B
- MLOps platform database
- CSV or Excel CRM-ready delivery
THE COMPLETE GUIDE
Best Fit Use Cases for Machine Learning Software Data
A short guide for B2B teams that sell into machine learning and MLOps work.
01
Where machine learning software data fits best
This list suits B2B teams that need to reach companies by the ML tools they run. That covers ML frameworks, cloud ML, MLOps tools and model training. It shows who uses TensorFlow, AWS SageMaker, Azure Machine Learning, Hugging Face, MLflow and H2O.ai.
It works well for a TensorFlow users contact database and companies using AWS SageMaker. Teams also use it for an Azure Machine Learning users list, a Hugging Face customers database, MLflow users contact data, an H2O.ai customers list and an ML engineers email list B2B.
You can also build an MLOps platform database, a list of companies building AI models and verified machine learning platform contacts. Use it for AI governance, model risk, cloud AI, data engineering, model monitoring, partner recruitment and research.
02
How to use the dataset for campaigns
First, pick the ML platform. Choose TensorFlow, AWS SageMaker, Azure Machine Learning, Hugging Face, MLflow, H2O.ai, Kubeflow or Databricks Mosaic AI. Then pick the work that fits your offer, such as training, deployment, MLOps, model tracking, AutoML, monitoring or generative AI.
Next, pick the roles: ML engineer, data scientist, MLOps or AI engineer, CDO, CTO, VP Engineering, AI product manager or head of data science. Then narrow by industry, size, revenue, region, cloud and company type.
Last, use the list for cold email, calls, LinkedIn, ABM, partner outreach, CRM updates or research. Does your offer depend on the ML platform a company runs? Then start here.
FAQS
Machine learning data FAQs
Straight answers about how the data is built, checked and delivered.
It is a verified B2B list of companies that use ML frameworks, cloud ML, MLOps tools and model training and deploy systems. Each record has company details, buyer contacts, the tool in use, industry and location. It is ready to load into a CRM for sales, ABM or AI consulting.
Yes. We build it around your industry, region, company size, job titles and goal. It suits MLOps, AI infrastructure, model deploy, data engineering, monitoring and AI governance offers.
Yes. SageMaker users suit offers on cloud AI consulting, MLOps, model monitoring, AWS security, data pipelines and AI governance.
Yes. It helps Microsoft partners, AI consultants and cloud data firms reach companies that train and run models on Azure ML.
Yes. It helps AI vendors and consultants reach companies that use Hugging Face for text AI, generative AI and model hosting.
Yes. It helps vendors reach companies that use MLflow to track experiments, version models and manage the model lifecycle.
Yes, alongside Vertex AI, Azure Machine Learning and Databricks users. If the product is niche or legacy, the free 100-record sample shows how many companies we can confirm before you buy anything.
Yes. It works as a machine learning mailing list for events and campaigns, and for teams selling ML data products such as labelled datasets and feature stores.
QUESTIONS THAT BRING BUYERS TO THIS PAGE, ANSWERED PLAINLY
Yes. It helps vendors reach companies that use H2O.ai for AutoML, forecasts and model training.
It lists the technical contacts who own ML models. They run MLOps, data science setups, model deploys, monitoring and AI pipelines.
It lists companies that use software to run ML operations. That covers experiment tracking, model registry, deploys, monitoring and rules.
Yes. This data helps you reach firms that build, train, deploy or manage ML and AI models today.
They are business contacts at companies that use ML platforms. Most are ML engineers, data scientists, MLOps and AI engineers, CTOs, CDOs and VP Engineering leads.
Most often as a CSV or Excel file. We can shape it for your CRM, email tool, sales platform or ABM system.
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