Hello, I’m reaching out because we are currently evaluating QVAC as a possible foundation for a privacy-first health AI product, and we would like to better understand the technical scope of what is available today. We are not looking only for a standalone consumer health app. We are building our own health platform with a fully custom methodology, proprietary interpretation framework, and our own structured dataset. Our stack includes: - a proprietary knowledge base, - custom health reasoning logic, - internal rules and axioms, - curated Q&A datasets, - domain-specific interpretation workflows, - and user-specific health context that we want the system to process in a controlled and consistent way. In other words, our interest is not just in using AI inside a health app, but in building our own health intelligence layer on top of a local/private AI stack. Because of that, we would like to clarify the following: 1. Is QVAC Health available only as a standalone end-user application, or do you also offer it as an SDK, white-label framework, embeddable product layer, or reusable application foundation for third-party teams? 2. If QVAC Health itself is not exposed as an SDK, can developers still build a fully custom branded health application on top of QVAC while reusing any of the underlying health-related infrastructure, data flows, local AI capabilities, or app components? 3. Does the QVAC SDK support integration of custom models, custom adapters, or fine-tuned domain-specific reasoning layers? 4. Can QVAC be used with a proprietary dataset and a custom interpretation framework, so that the resulting application follows our own health logic rather than a generic wellness model? 5. Is there support for combining: - local on-device AI, - a proprietary structured knowledge base, - user-specific health data, - and custom application logic within one product architecture? 6. Do you provide developer documentation, architectural guidance, or implementation examples for teams building their own health product on top of QVAC SDK? 7. Is it possible to maintain a fully custom data model, custom workflows, and custom UX while still relying on QVAC as the underlying local AI platform? 8. More specifically, can QVAC support a setup where the application uses: - our own branded frontend, - our own health ontology, - our own reasoning rules, - our own user-state model, - and our own proprietary dataset while keeping processing local and privacy-preserving? From our perspective, the key question is whether QVAC should be understood as: - a standalone health app for end users, or - a developer platform that can power a fully custom health AI application with third-party domain intelligence. If useful, we would be happy to share more detail about our intended architecture and the type of dataset and reasoning framework we are working with. Thank you in advance. We would appreciate any technical clarification you can provide. Best regards, Filip