> For the complete documentation index, see [llms.txt](https://whitepaper.nativelyai.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://whitepaper.nativelyai.com/introduction.md). # Introduction NativelyAI is building the execution layer for **AI-native application creation** - a paradigm where software is generated directly from user intent, and where **privacy, sovereignty, and orchestration** replace manual development, fragmented tooling, and black-box model providers. The platform enables individuals, teams, and enterprises to turn any idea into a production-ready application instantly, without writing code and without exposing sensitive data to external systems. The shift to AI-generated software demands infrastructure that can understand intent, enforce data boundaries, route workloads optimally, and deploy reliably across clouds, VPCs, and decentralized compute. NativelyAI provides this through an integrated stack that unifies **natural-language understanding, AI orchestration, sovereign execution, and automated deployment**, forming a complete operating system for private AI-driven development. --- # 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 dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://whitepaper.nativelyai.com/introduction.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. 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.