IBM Cloud Forum 2020
Cloud computing paired with industry expertise can improve your agility and sustainability
Measure and track AI outcomes
Track performance of production AI and its impact on business goals, with actionable metrics, in a single console.
Tune your AI for business
Apply business results to create a continuous feedback loop that improves and sustains AI outcomes.
Govern and explain AI
Maintain regulatory compliance by tracing and explaining AI decisions across workflows, and intelligently detect and correct bias to improve outcomes.
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.
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.
Predict CSP asset failures
Data scientists can build machine-learning models and work with their IT operations teams to confidently recommend proactive asset maintenance for communications service providers (CSPs).
Documentation and resources
Build and train AI models and prepare and analyze your data — all in a single, integrated environment.
Get started with Watson OpenScale
Explore the capabilities of Watson OpenScale — the open platform that helps enable businesses to automate and operate AI at scale, wherever it resides. Get insights into every stage of the AI lifecycle and give your business greater confidence in AI outcomes.