# 5.1 High-Level Architecture Visuallyze’s architecture is built around the principle that AI workflows should be represented, executed, and verified across independent but interoperable components. At the top of the stack sits the client layer—a visual environment backed by a graph engine that allows users to articulate complex workflows in a structured format. Beneath this lies the orchestration layer, which transforms these visual specifications into executable training and inference tasks and coordinates their distribution across compute nodes. Parallel to this, the on-chain layer provides the canonical record of workflows, models, and lineage, ensuring that every significant event in the model lifecycle is verifiable and immutable. Execution occurs across a heterogeneous network of off-chain compute providers. These providers interact with the orchestration layer via standardized job protocols and are compensated based on validated contributions. Data artifacts, training checkpoints, and final model weights reside in storage layers referenced by content hashes on Solana. Marketplace interactions, governance actions, and resource allocation flows are similarly executed through on-chain logic, making the overall system both decentralized and accountable. The entire platform functions as a coordinated ecosystem rather than a centralized application. --- # Agent Instructions: 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: ``` GET https://docs.visuallyze.xyz/5.-system-architecture/5.1-high-level-architecture.md?ask= ``` The question should be specific, self-contained, and written in natural language. 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.