> For the complete documentation index, see [llms.txt](https://docs.glbnxt.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.glbnxt.com/faq/security-and-data-sovereignity/can-we-use-third-party-ai-models-and-what-are-the-data-implications.md). # Can we use third-party AI models, and what are the data implications? GLBNXT does not share your data with third-party AI providers as part of its standard operation. All processing takes place within your sovereign environment by default. However, GLBNXT's model hub includes a selection of models that are provided exclusively through a direct connection with third-party AI providers. Customers can choose to use these models, but doing so means that data submitted in those interactions is processed under the terms and conditions of that external provider, not within your sovereign GLBNXT environment. These models are available in the hub for specific use cases, including testing, evaluation, or situations where a particular third-party model offers capabilities your team wants to explore. The option exists by deliberate choice, not by default. If you are considering using a third-party model, it is essential that your organisation reviews and understands the terms and conditions of that provider before doing so, including their data handling, retention, and privacy policies. Choosing to use a third-party model is done at your organisation's own risk, and GLBNXT cannot be held responsible for how external providers handle data submitted through their services. In many cases, GLBNXT can advise on comparable models that deliver similar performance while remaining fully within your sovereign environment. Before reaching for a third-party option, we recommend speaking with your GLBNXT account team. The right sovereign alternative is often already available in your environment. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation by asking a question. Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters: ``` GET https://docs.glbnxt.com/faq/security-and-data-sovereignity/can-we-use-third-party-ai-models-and-what-are-the-data-implications.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case. 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.