If you’re reading this, you’re likely one of the multitudes of people that are eagerly building and deploying AI models to help streamline operations, reduce costs, and offer customers and employees new and personalized experiences. You’re also probably wondering how best to govern all of the AI use cases you and your organization are deploying. Easy answer? Collibra AI Governance of course.
Collibra AI Governance lets you catalog, assess and monitor any AI use case for improved AI model performance and reduced data risk. There are a variety of inputs that go into an AI use case including the data that feeds it, the business context of the use case, as well as the actual model itself. AI models can vary greatly in their use and complexity – everything from decision tree models to complex large language models (LLMs). Regardless of what kind of models you already have in place or what your future plans you have for new GenAI models, governing AI from the start will help you reduce risk and maximize value.
To ensure model information can be ingested into Collibra AI Governance, we’re continuing to expand integrations into the top ML platforms. We’re excited to announce the public beta of integrations for Amazon Sagemaker and Microsoft Azure AI, two prominent platforms used by Collibra customers.
By integrating with both Amazon Sagemaker and Microsoft Azure AI, users will be able to see a summary view of all aspects of the use case, including the model, in a single location, providing explainability and trust without the need to traverse applications and interfaces.
Want to get started? Head over to our documentation to learn more about the Amazon Sagemaker integration beta and Microsoft Azure AI integration beta.
