New partnership with Palantir

Unlock valuable data across your hybrid data estate and easily use AI to make more informed decisions.

Learn about the partnership

Build AI with IBM Watson Studio, implement across any cloud

Benefits↓     Features↓     Client stories↓      AI with IBM Cloud Pak for Data↓

Build, run and manage AI models, and optimize decisions at scale across any cloud. IBM Watson Studio empowers you to operationalize AI anywhere as part of IBM Cloud Pak® for Data, the IBM data and AI platform. Unite teams, simplify AI lifecycle management and accelerate time to value with an open, flexible multicloud architecture.

Realize results faster:

  • Automate AI lifecycles with ModelOps pipelines
  • Speed data science development with AutoAI
  • Prepare and build models visually and programmatically
  • Deploy and run models through one-click integration
  • Promote AI governance with fair, explainable AI
  • Drive better business outcomes by optimizing decisions

→ Read the Forrester report

Use open source frameworks like PyTorch, TensorFlow and scikit-learn. Bring together the development tools including popular IDEs, Jupyter notebooks, JupterLab and CLIs — or languages such as Python, R and Scala. Get started here.

Benefits

Accelerate deployment time

Unify tools, processes and talent. Monitor models for bias, trust and transparency.

See how Highmark Health quickly predicts at-risk patients

Boost customer segmentation depth

Fully integrate machine learning into business. Speed data preparation and model development with AutoAI.

See how Wunderman-Thompson creates better experiences

Minimize errors

Design smarter distribution. Speed inventory movement and reduce costs.

See how Fleetprice made packing tasks 99.5% error-free

Optimize AI and cloud economics

Put multicloud AI to work for business. Use flexible consumption models. Build and deploy AI anywhere.

Read the ESG report

Predict outcomes and prescribe actions

Optimize schedules, plans and resource allocations using predictions. Simplify optimization modeling with a natural language interface.

Watch how (07:06)

Synchronize apps and AI

Unite and cross-train developers and data scientists. Push models through REST API across any cloud environment. Save time and the costs of managing disparate tools.

Read the 451 Research report

Unify tools and increase productivity for ModelOps

Operationalize enterprise AI across clouds. Govern and secure data science projects at scale.

Learn what’s new in deployment (link resides outside IBM)

Deliver fair, explainable AI

Reduce model monitoring efforts by 35% to 50%. Increase model accuracy by 15% to 30%. Increase net profits on a data and AI platform.

Quantify the value of explainable AI

Comply with regulations and manage risks

Protect against exposure and regulatory penalties. Simplify AI model risk management through automated validation.

View the infographic (PDF, 133 KB)

Features

Automatically build model pipelines with AutoAI

Prepare data and select model types. Generate and rank model pipelines.

Discover AutoAI

Prepare, explore and refine data

Use the data refinery tool to cleanse and shape data with a graphical flow editor. Apply interactive templates to code operations, functions and logical operators.

Start data preparation

Bring your open source notebooks

Create a notebook file, use a sample notebook or bring your own notebook to IBM Watson Studio. Code and run a notebook.

Create Jupyter notebooks

Simplify modeling with SPSS Modeler

Prepare data quickly and develop models visually with IBM® SPSS® Modeler in IBM Watson Studio.

Use drag-and-drop models

Run and train models

Build experiments quickly and enhance training by optimizing pipelines and identifying the right combination of data.

Code and run a notebook

Deploy and monitor models

Bring your model of choice to production. Track and retrain models using production feedback.

Read the supported framework

Combine predictive and prescriptive models

Use predictions to optimize decisions. Create and edit models in Python, in OPL or with natural language.

Optimize decisions

Monitor quality, fairness and drift metrics

Select and configure deployment for model insights. Customize model monitors and metrics.

Prepare for model monitoring

Compare and evaluate models

Evaluate and select models with new data. Examine the key model metrics in a side-by-side comparison.

Manage model risk

Client stories

Man running on a track

Wunderman Thompson Data

Learn how Wunderman Thompson built a scalable, efficient machine learning pipeline to drive high-volume predictions with AutoAI.

See the webinar

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JP Morgan Chase

Discover how JP Morgan Chase improved model risk management with IBM Watson Studio.

Watch the video (01:37)

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Geisinger Health System

Learn how Geisinger Health System identified traits associated with a higher risk of mortality to develop more effective treatments.

View the case study

IBM Cloud Pak for Data workflow, including collecting and preparing data, building and deploying AI models and optimizing decisions.

Deploy your AI with IBM Cloud Pak for Data

IBM Watson Studio helps you build and scale AI with trust and transparency by automating AI lifecycle management. It empowers you to organize data, build, run and manage AI models, and optimize decisions across any cloud using IBM Cloud Pak for Data. Deploying AI with continuous model governance enables you to accelerate time to discovery, prediction and outcomes while keeping AI explainable and tuned to your business demand.

Building on the hybrid-cloud foundation of Red Hat® OpenShift®, IBM Watson Studio on IBM Cloud Pak for Data simplifies the process of deploying almost any open source project to production with containerized resource and infrastructure management efficiency.

→ Read the IDC report

→ Explore IBM Cloud Pak for Data

Related products

IBM Watson Studio Premium

Empower your organization to optimize decisions, increase productivity through visual modeling and get more from your data investments.

Learn more

IBM Cloud Pak for Data

Collect, organize and analyze data with a multicloud data and AI platform. Create an analytics foundation for easier access to data. Scale insights on demand.

Learn more

IBM Watson OpenScale™

Manage and monitor models with explainable, trusted AI. Ensure model fairness, detect model drift and mitigate model risk.

Learn more

What’s new

Man seated at desk looking at computer

Explore multicloud ModelOps

Get our ModelOps newsletter, which includes research from Gartner. Learn how to get AI working in your operations faster.

Read the newsletter

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Synchronize AI and DevOps

Explore the key capabilities for AI-led development and why you should integrate AI models into development cycles in this Aberdeen study.

Read the research

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Get up to speed on AI governance

Explore what AI governance is and why it matters. Make AI trustworthy.

Download the ebook

Find out more

  • Take advantage of machine learning and AI to analyze your data

  • Start for free

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Book a consultation with one of our experts.

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