> For the complete documentation index, see [llms.txt](https://azen-protocol.gitbook.io/azen-gitbook/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://azen-protocol.gitbook.io/azen-gitbook/azen-protocol/computing-architecture-and-incentive-mechanism.md).

# Computing Architecture & Incentive Mechanism

**aZen Protocol provides a modular, scalable, and autonomous computing environment by integrating dfNFTs, AI agents, and smart contract-driven orchestration.**

* dfNFT-Based Computation & AI Resource Market
  * Users can tokenize, trade, and deploy AI models, applications, and computational power.
  * Smart contract automation ensures optimal pricing and transparent execution.
* AI Agent-Driven Computation Layer
  * AI Agents predict workload requirements and allocate compute resources dynamically.
  * Smart contract-based automation reduces inefficiencies and ensures optimal utilization.
* Privacy-Preserving AI Computation
  * Zero-knowledge proofs (ZKP) and homomorphic encryption ensure AI computations remain secure and verifiable.
  * Privacy-preserving ML (PPML) enables decentralized AI model training while maintaining data privacy.
* AI-Optimized Tokenomics & Incentive Models
  * AI-driven models dynamically adjust staking, token pricing, and compute resource allocation.
  * Users contributing computational power, AI services, or dApps are rewarded via tokenized incentives.