> For the complete documentation index, see [llms.txt](https://documentations.seclea.com/seclea-user-documentation/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://documentations.seclea.com/seclea-user-documentation/introducing-seclea/seclea-building-trust-in-ai/seclea-integrations-and-supported-frameworks.md).

# Seclea integrations and supported frameworks

Seclea platform provides integration with several machine learning frameworks and libraries, including TensorFlow, PyTorch, and Scikit-Learn. It also supports a wide range of deployment options, including cloud, on-premises, and hybrid deployments.

Seclea is a comprehensive AI assurance platform that supports a wide range of machine learning and deep learning algorithms. It provides tools for AI fairness, transparency, explainability, accountability, and risk management. Additionally, Seclea supports AI number explainability tools to ensure that organisations can explain how an AI algorithm arrived at a specific output.

The platform also has built-in support for various AI regulatory frameworks such as the European Union's Artificial Intelligence Act, Canada's Artificial Intelligence and Data Act, and the US Food and Drug Administration's guidelines for AI-based Software as a Medical Device, among others. With these integrations and supported frameworks, Seclea offers a comprehensive AI platform for responsible and compliant AI development and deployment.

Overall, Seclea empowers organizations to develop and deploy AI applications with confidence and assurance that they are compliant with global regulatory frameworks and ethical guidelines.


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