> For the complete documentation index, see [llms.txt](https://docs.sweep.finance/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.sweep.finance/ecosystem-components/tokenization.md). # Tokenization ### **Overview of Tokenization** Tokenization within the Sweep ecosystem is designed to enable the creation of structured, programmable value systems that extend beyond standard interaction models. Rather than being limited to fixed platform mechanics, tokenization introduces a flexible framework where value can be represented, segmented, and interacted with through digital units. These units are not isolated assets, but components of broader structures that define how participation and value distribution are organized. At its core, tokenization allows the transformation of both system-defined and real-world value into modular and accessible formats, enabling users to interact with systems that were previously static or inaccessible. Through this approach, participation is no longer restricted to predefined interactions, but can expand into more dynamic and structured forms. The system is designed to support value-linked structures, where digital units are connected to underlying activities, systems, or external references. This enables a more flexible representation of value while maintaining a consistent and transparent framework, allowing external value sources to be integrated into the ecosystem over time. Unlike traditional token models that focus on simple ownership representation, Sweep’s tokenization approach focuses on participation and structured interaction, allowing users to engage with value in a more active and programmable way. By integrating tokenization into its architecture, Sweep expands from a system of interactions into a broader economic framework, where value can be introduced, distributed, and interacted with in new and scalable ways. --- # 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://docs.sweep.finance/ecosystem-components/tokenization.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.