# What model CBC is using ? CBC AI employs the power of TensorFlow and Keras, two open-source libraries extensively used in the machine learning and deep learning space. Our deep learning models are constructed on these robust platforms, enabling us to tackle complex AI tasks efficiently and effectively. As a company, we're dedicated to embracing open-source technologies. This approach not only ensures transparency and fosters community-driven innovation but also allows us complete ownership of our models. By building on TensorFlow and Keras, we can fully comprehend, tailor, and enhance our models as required. This is central to our philosophy of being self-reliant and committed to continual growth and improvement in the AI domain. Our alignment with open-source principles and practices reaffirms our dedication to being at the forefront of AI research and development, while also fostering a collaborative ecosystem where knowledge and technology become universally accessible and beneficial. --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://cbcai.gitbook.io/cbc-ai/what-model-cbc-is-using.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.