# 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.


---

# 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://azen-protocol.gitbook.io/azen-gitbook/azen-protocol/computing-architecture-and-incentive-mechanism.md?ask=<question>
```

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.
