Deploy and run AI models with Watson Machine Learning

As part of IBM Watson® Studio, IBM Watson Machine Learning helps data scientists and developers accelerate AI and machine learning deployment on IBM Cloud Pak® for Data. Deploy AI models at scale across any cloud on an open, extensible architecture. With IBM you can:

  • Deploy any models including machine learning and deep learning models and decision optimization models
  • Dynamically retrain models with continuous learning
  • Automatically generate APIs to build AI-powered applications through DevOps
  • Manage and monitor models for model drift, bias and risk
  • Bring any projects into production, including open source, third-party and IBM tools

Unleash the power of Watson AI technologies. Automate the AI lifecycle for ModelOps.
→ Watch data science on-demand webinars (link resides outside IBM)
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Deployment options

IBM Cloud Pak for Data

Deploy Watson Machine Learning as part of a multicloud data and AI platform.

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Watson Machine Learning on IBM Cloud Pak for Data as a Service

Deploy and run AI models in the IBM Cloud®.

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Watson Machine Learning simplifies and speeds deployment at scale

Learn the economic impact of Watson Studio and IBM Watson® Knowledge Catalog

Moving beyond experimentation and maintaining production-level accuracy of AI models are still big challenges. Watson Machine Learning can accelerate the time to value of any model, with a projected ROI of 459% over three years, with payback in less than six months.¹

51%

find optimizing, sustaining and expanding AI capabilities challenging²

80%

of AI pioneers are investing in the process to train algorithms³

Watson Machine Learning features

AutoAI: AI lifecycle management

Gain consistency and repeatability of end-to-end AI lifecycle management with AutoAI.

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One-click deployment

When you are ready, save and select services to deploy. Get started with experimentation, evaluation and deployment.

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Model operations

Use a machine learning framework for saving, deploying and versioning models, and for deployment of infrastructure management.

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Integrated UI end-to-end

Automate data prep, advanced data refinery and model explainability with Watson Studio and Watson Machine Learning.

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Deploy any model at scale

Bring your favorite data science tools — open source, IBM SPSS® Modeler or Watson Studio.

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Dynamic retraining

Enable continuous learning and automatically retrain your model to maintain model quality.

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IBM named a Leader in The Forrester Wave™

Read evaluations of the key vendors in predictive analytics and machine learning.

Read the report

What’s new with Watson Machine Learning

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On-demand webinar: What’s new with data science

See how you can deploy deep learning and ML models anywhere.

→ Dig deeper (link resides outside IBM)

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AutoAI playlist: Watson Machine Learning deployment

Watch tech experts in AutoAI videos, take product tours and explore hands-on labs.

→ Learn AutoAI today

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ESG white paper: Predict and Optimize

Read the analyst testing of Watson Studio on IBM Cloud Pak for Data.

→ Get the technical validation

Watson Machine Learning in action

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Anyline

Train and deploy deep learning models for offline optional character recognition (OCR) on mobile and embedded devices in record time.

→ Watch the video (01:30)

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Caixa Geral de Depósitos France

Accelerate customer service by delivering faster decisions using an innovative hybrid cloud application enabled by machine learning.

→ Read the case study

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KIST Europe

Explore how machine learning can automate quality management processes, reduce defect rates and save costs.

→ Read the case study

Product images

Screenshot of Watson machine Learning server execution and deployment

Watson Machine Learning Server execution and deployment: Save branch as a model from SPSS Modeler flows within Watson Studio
Screenshot of Watson Machine Learning model deployment status

Model deployment status: Review status, date and originator to assess models
Screenshot of Watson Machine Learning runtime location

Runtime location: Select a runtime location to run your modeler flow
Screenshot of Watson Machine Learning one-click deployment

One-click deployment: Save the model of your choice and click to deploy with Watson Machine Learning
Screenshot of Watson machine Learning server execution and deployment

Watson Machine Learning Server execution and deployment: Save branch as a model from SPSS Modeler flows within Watson Studio

Screenshot of Watson Machine Learning model deployment status

Model deployment status: Review status, date and originator to assess models

Screenshot of Watson Machine Learning runtime location

Runtime location: Select a runtime location to run your modeler flow

Screenshot of Watson Machine Learning one-click deployment

One-click deployment: Save the model of your choice and click to deploy with Watson Machine Learning

Get started with Watson Machine Learning

What will we deploy together?

See pricing options and the latest news and details to start developing machine learning models today.

See pricing and details

See the latest data science and AI news

Compare features
  Watson Machine Learning Conventional ML tools
Hybrid multicloud deployment   
Integrated with AutoAI   
Prescriptive analytics solvers   
Visual data science deployment
Access to data preparation
Advanced data refinery   
Dynamic continuous learning   
Neural network search   
1-click open-source deployment   
Automated AI lifecycle mgmt.   
Monitoring and debiasing   
Natural language integration   
Visual recognition service   

Related products and offerings

IBM Watson Studio

IBM Watson Studio provides tools to work more easily and collaboratively with data to build and train models at scale. It gives you the flexibility to build models where your data resides and to deploy anywhere in a hybrid environment so you can operationalize data faster.

IBM Cloud Pak for Data

IBM Cloud Pak for Data helps you collect, organize and analyze data with a multicloud platform. It creates a trusted analytics foundation that makes data easier to access and enables you to scale insights on demand with AI.

IBM Decision Optimization

IBM Decision Optimization provides tools that use mathematical and computational sciences to help data scientists optimize machine-learning decisions. Decision optimization models can now be more easily deployed as a service inside Watson Machine Learning.

IBM Watson® OpenScale™

IBM Watson OpenScale tracks and measures outcomes from AI across its lifecycle and adapts and governs AI to changing business situations — for models built and running anywhere.

Deep learning

The deep learning service within IBM Watson Studio helps data scientists visually design neural networks and scale out training runs while paying only for the resources utilized.

IBM SPSS Modeler

IBM SPSS Modeler empowers an enterprise to use drag-and-drop data science to accelerate time to value for production-scale models.

IBM Watson Studio Desktop

Watson Studio Desktop helps anyone get started with model building and deployment from the desktop — anytime, anywhere.

IBM Watson Machine Learning Accelerator

Watson Machine Learning extends machine learning and deep learning model deployment in a multitenant, distributed environment.

Expert resources to help you succeed

Community

Get technical tips and insights from other users in the Watson Studio community.

Documentation

Find answers on machine learning in the IBM Cloud Pak for Data documentation.

Support

Learn more about technical support.

Footnotes

¹ 2018 Forrester The Total Economic Impact™ of IBM Watson Studio and Watson Knowledge Catalog (PDF, 715 KB)

² 2019 Forrester Infographic “AI Experiences A Reality Check” (link resides outside IBM)

³ 2018 MIT Sloan Review (link resides outside IBM)