> For the complete documentation index, see [llms.txt](https://artisan-ai.gitbook.io/docs/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://artisan-ai.gitbook.io/docs/how-it-works/technical-architecture-under-artisanai.ai.md).

# Technical Architecture Under ArtisanAI.ai

*Protocol-Level Design Principles & Execution Model*

#### Identity as the Root Protocol Primitive

Identity is managed through wallet-based authentication, serving not only as login but as the anchor for authorship, permissioning, and on-chain reputation. Every act — creation, remix, syndication — is signed and indexed to the wallet, enabling trustless attribution and traceable reputation paths.

#### Modular Inference Execution Layer

Model execution is handled through a modular runtime. Developers can deploy or link models — including transformers, diffusion pipelines, and LLMs — and route inference via on-chain or off-chain compute. Usage is logged, metered, and paired with immutable metadata (model ID, prompt hash, timestamp).

#### Decentralized & Permissioned Storage

Assets are encrypted at the client level and stored via decentralized systems like IPFS or Arweave. Smart contracts manage access control, license types, and remix permissions, ensuring wallet-linked storage sovereignty and content-level programmability.

#### Token-Linked Metering & Incentivization

Economic flows are tied to protocol usage. Each model call, content remix, or curation event triggers automatic $ART distribution, rewarding creators, model deployers, and infrastructure contributors according to deterministic rules and recorded impact.

#### Programmable Extensibility & Open Stack

All core capabilities — identity, attribution, inference, vault, reward — are exposed as permissionless smart contracts and APIs. This design allows external developers, DAOs, and apps to fork, extend, or compose against ArtisanAI, turning it into a public creative execution layer.

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