Explore the analyst report

IBM is a leader in The Forrester Wave™: Multimodal Predictive Analytics and Machine Learning, Q3 2020

Operate trusted AI. Monitor and manage models.

Businesses are increasingly reliant on AI to speed decision making and streamline operations. Successful AI adoption relies on trust and transparency in how models are built, deployed and managed.

IBM Cloud Pak® for Data helps you gain trust and transparency in AI. IBM Watson® OpenScale™, a capability within IBM Watson Studio on IBM Cloud Pak for Data, monitors and manages models to operate trusted AI. With model monitoring and management on a data and AI platform, an organization can:

  • Monitor model fairness, explainability and drift
  • Visualize and track AI models in production
  • Validate and test models to mitigate regulatory, reputational and operational risks
  • Increase end-to-end visibility of AI lifecycles

→ Read the Forrester report

→ Register for the IBM Innovation Preview virtual event: Trust in AI (link resides outside IBM)

Turn open source frameworks and tools into trusted AI models with IBM Cloud Pak for Data.

Use cases

Credit risk modeling

Credit lenders can monitor risk models for performance, bias and explainability to limit risk exposure from regulations and create more fair and explainable outcomes for customers.

Credit risk modeling use case diagram

Explainable claims processing

Insurance underwriters can use machine learning to more consistently and accurately assess claims risk, ensure fair outcomes for customers and explain AI recommendations for regulatory and business intelligence purposes.

Explainable claims use case diagram

Predict CSP asset failures

Communications service providers can recommend proactive asset maintenance using real-time model monitoring.

CSP asset failure use case diagram

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Explore model monitoring and model management. Get model insights and give your business greater confidence in AI outcomes.