Use cases
When you implement the watsonx.ai and watsonx.governance use cases, you can solve the challenges of building machine learning models and generative AI, governing AI, and managing your AI lifecycles.
The use cases in IBM watsonx as a Service provide these main capabilities for managing and automating your AI lifecycles:
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Collaborative innovation
Collaborate with others to discover insights. Prepare data, analyze data, and build models with a set of integrated tools for all levels of experience. -
Governance and compliance
Track and document the detailed history of AI models to help ensure compliance. -
Unified lifecycle
Automate the building, testing, deploying, and monitoring of AI models.
You can start with a use case and add another one as you need it. Explore each use case to learn about what you can accomplish and the tools you can use.
Watsonx.ai
Transform your business processes with AI-driven solutions by integrating machine learning and generative AI into your operational framework. Watsonx.ai provides the processes and technologies to enable your enterprise to develop and deploy machine learning models and generative AI solutions.
Services for this use case: Watson Studio and Watson Machine Learning
See the watsonx.ai use case.
Watsonx.governance
Drive responsible, transparent, and explainable AI workflows with an integrated system for tracking, monitoring, and retraining AI models. Watsonx.governance provides the processes and technologies to enable your enterprise to monitor, maintain, automate, and govern machine learning and generative AI models in production.
Services for this use case: Watson Studio, Watson Machine Learning, and Watson OpenScale
See the watsonx.governance use case.
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Parent topic: Overview of watsonx