Now available: AutoAI on Watson Studio Cloud

What is AutoAI? Why Now?

Strategic investments in AI can be a game changer. To fulfill the promise of AI, organizations are tackling skillset gaps, deployment and governance processes today.

To help simplify an AI lifecycle management, AutoAI automates:

  • Data preparation
  • Model development
  • Feature engineering
  • Hyper parameter optimization

AutoAI is available within Watson Studio with one-click deployment via Watson Machine Learning. Use it with Watson OpenScale to track and measure AI outcomes together with the Watson Studio family.

AutoAI benefits

Fast model selection

Select top-performing models in only minutes.

Start quickly

Get started with experimentation, evaluation and deployment.

AI lifecycle management

Enforce consistency and repeatability of end-to-end ML and AI development.

AutoAI features

Integrated UI

Automate data prep, feature engineering and hyper-parameter optimization.

Pipeline leaderboard

Watch and compare the top performing models on the leaderboard.

One-click deployment

When you are ready, save and select services to deploy with Watson Machine Learning.

What’s new with AutoAI

Video featuring an IBM fellow discussing the revolution in automating AI.

Watch the video: Automation of AI

Ruchir Puri discusses the next revolution in automating AI. Learn how to automate the task of building, deploying, and managing AI tasks.

Image of woman working at desk with three different monitors.

On-demand Webinar: AI for AI – Introducing AutoAI with Watson Studio

View how you can automate and operationalize AI across the data science lifecycle with AutoAI today.

Enterprise Strategy Group logo for hybrid multi-cloud artificial intelligence: IBM Watson Studio and Watson machine learning.

Analyst video: Hybrid multicloud AI at scale with IBM Watson Studio

Watch how AutoAI/ML is integrated with IBM Watson Studio and Watson Machine Learning to operationalize AI in this on-demand video.

Talk to an expert

Schedule a one-on-one consultation with an AutoAI expert

Comparison Table

AutoAI vs. AutoML
  AutoAI Traditional AutoML
Transfer learning   
Neural network search   
Data preparation
Advanced data refinery   
Feature engineering
Hyper parameter optimization
One click deployment   
Explainability and de-biasing   
AI lifecycle management   

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