> For the complete documentation index, see [llms.txt](https://docs.lazai.network/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.lazai.network/lazai-workflow-and-runtime/dat-specifications-and-flow.md).

# DAT Specifications & Flow

LazAI’s Data Anchoring Token (DAT) is a semi-fungible token (SFT) standard designed for AI dataset anchoring, licensing, and AI model provenance tracking. This protocol introduces a multi-layered ownership model, ensuring composability, structured access control, and verifiable AI asset usage in a decentralized ecosystem.

<figure><img src="/files/r6MqZanfEEUDPn45aaMe" alt=""><figcaption></figcaption></figure>

LazAI’s Data Anchoring Token (DAT) protocol redefines AI dataset ownership, licensing, and provenance tracking by integrating semi-fungible tokenization, on-chain verification, and decentralized AI economy models.

* **AI-Composable Economy:** Enables dataset/model composability for seamless AI evolution.
* **Verifiable AI Assets:** Ensures trustless authentication through cryptographic proofs.
* **Privacy-Preserving AI Training:** Supports ZK-protected AI model development.
* **AI Data Exchange & Monetization:** Unlocks new AI business models, allowing transparent revenue sharing.

This AI-first SFT standard establishes a scalable, trustless AI asset ecosystem, distinct from previous tokenization models.


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