Gen AI has the potential to boost productivity and unlock trillions in economic value. However, these models come with new complexities and risks. Regardless of whether you are using gen AI models or traditional ML models, every model needs governance.
IBM® watsonx.governance™ toolkit for AI governance provides users with model choice and flexibility. This toolkit can be used to govern gen AI models that are built on IBM® watsonx.ai™ and models that are developed on third-party platforms, including Amazon Bedrock, Microsoft Azure and OpenAI. With watsonx.governance, you can also govern ML models built in third-party tools. Clients can choose between cloud or on-premises deployments for both model types.
We’ll be there to answer your questions about generative AI strategies, building a trusted data foundation, and driving ROI.
Access an enterprise-ready, multi-model toolset on a single integrated platform that automates governance for both gen AI and ML models.
Automate tools and processes throughout the AI lifecycle to reduce manual errors and accelerate AI development safely and responsibly.
Deliver transparent model processes to improve accuracy, fairness, and explainability and provide clear documentation of model health and functions.
To govern an enterprise's gen AI effectively, it is essential to monitor and mitigate the newly amplified risks originating from models, users, data sets and regulations. Watsonx.governance offers 3 key capabilities for achieving this.
Get started scaling AI responsibly for both generative AI and ML models.
IBM’s statements regarding its plans, directions, and intent are subject to change or withdrawal without notice at IBM’s sole discretion. See Pricing for more detail. Unless otherwise specified under Software pricing, all features, capabilities, and potential updates refer exclusively to SaaS. IBM makes no representation that SaaS and software features and capabilities will be the same.