> For the complete documentation index, see [llms.txt](https://docs.xyxyx.pro/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.xyxyx.pro/tokenization-models/a4.md). # A4 ### Overview The A4 tokenization model allows for the creation of text-based tokens in the A4 output format. * [Specifications](/tokenization-models/a4/specifications.md) *** ### Key Features #### Multiple Pages The A4 model is designed to consolidate multiple outputs into a single text-based token, incorporating a built-in pagination system. As a result, A4 enables the tokenization of documents with multiple pages. *** ### Intended Use Cases The A4 tokenization model is designed for tokenizing long text records (e.g., documents). It is intended for use cases where a document requires the highest levels of immutability, permanency, attestability, and auditability of text records. This is particularly applicable in critical contexts that demand the utmost data provenance and integrity. *** #### Legal A4 can be used for tokenizing traditional critical legal documents, such as contracts, financial statements, title deeds, and patents.

*** #### AI A4 can be integrated into AI-related frameworks, enabling the permanent recording of long text records generated during AI processes. This ensures unparalleled data provenance and integrity — from tokenizing AI model performance reports, explanation documents, and versioning, to tokenizing compliance audits, algorithmic intellectual property (IP), and data provenance and lineage.

*** #### Literature A4 can be used for tokenizing critical literature documents, such as research articles, academic papers, technical whitepapers, and manifestos.