Compute is metered, and usage is monetized.
In ArtisanAI, AI model inference is not a passive backend operation — it is a token-incentivized, programmable economic activity. The protocol treats each model as a first-class on-chain actor, with usage governed by deterministic rules, resource tracking, and monetization logic.
When a user initiates a content generation request (e.g., by submitting a prompt), the following sequence occurs:
Model Selection
The request is routed to either a public protocol-curated model or a user-deployed custom model.
Inference Execution
The selected model processes the input and generates output on distributed or edge compute.
Usage Logging
The model’s CID, user wallet, execution parameters, and timestamp are logged on-chain.
Metering & Cost Calculation
Based on complexity and compute consumption, the execution is priced in $ART tokens.
Settlement & Distribution
$ART tokens are programmatically distributed to the model creator, infrastructure operator, and protocol treasury.
The metering algorithm adjusts execution cost based on:
Model Type & Size
Inference Latency
Priority Tier
Storage Access
Concurrent Load
Model developers can configure monetization terms via smart contracts:
Fixed or tiered pricing curves
Access permissions
Remix licensing splits
Revenue streaming to DAO treasuries
All inference events are:
Recorded on-chain
Linked to input & output assets
Auditable & queryable
Incentive-linked
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