> For the complete documentation index, see [llms.txt](https://faia.liccium.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://faia.liccium.com/technology/implementation.md). # FAIA Reference Implementations FAIA supports different levels of implementation depending on the required level of persistence, verification, and infrastructure integration. ## FAIA Statement Generator The FAIA Statement Generator provides a lightweight mechanism for creating portable AI attribution statements using the FAIA vocabulary. The generated statements can be embedded into websites, attached to publications, or shared alongside digital content. They support both human-readable and machine-readable disclosure of AI involvement. However, these statements are not persistently bound to the content and are not independently verifiable. Without cryptographic signing, registry publication, and persistent content–metadata binding, there is no reliable mechanism to verify authorship, integrity, or long-term association with the underlying asset.
## Liccium Reference Implementation The Liccium platform provides a reference implementation of persistent and verifiable FAIA declarations. The implementation combines: * ISCC-based content fingerprinting * machine-readable JSON-LD declaration metadata * cryptographic signatures and verifiable credentials * declaration APIs * federated registry infrastructure Using the Liccium implementation, FAIA declarations can be: * created through applications or APIs * digitally signed by the declarant * persistently linked to digital content through ISCC identifiers * published to interoperable registry infrastructure * independently resolved and verified across platforms and workflows The implementation includes the Liccium Declaration API, registry infrastructure, and user-facing applications supporting declaration creation, signing, publication, and verification workflows. --- # 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://faia.liccium.com/technology/implementation.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.