> For the complete documentation index, see [llms.txt](https://everyai.gitbook.io/everyai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://everyai.gitbook.io/everyai/introduction/about-everyai.md).

# About EveryAI

## Project Introduction

EveryAI is the first decentralized AI service network combining DePIN and AI Agent technologies, aimed at providing low-cost, high-privacy, efficient, and open collaborative AI services through global idle computing resources (such as personal computers, mobile phones, IoT devices, etc.). The project's core philosophy is **"AI Everyone, Power to Everyone"**, seeking to break through centralized computing power monopolies and data hegemony, enabling users to be not just consumers of AI services, but also network builders and beneficiaries.

### **Key Features**

* **Inclusive AI**: By utilizing idle resources, dramatically reduce AI service costs, enabling individuals and enterprises to easily access AI capabilities.
* **Privacy First**: Employing federated learning, homomorphic encryption, and other technologies to ensure data is processed locally, preventing privacy leaks.
* **Intelligent Agency**: AI Agents automate task allocation and execution, providing personalized recommendations and optimizing user experience.
* **Physical Resource Network**: Based on DePIN principles, constructing a decentralized physical infrastructure network that incentivizes users to contribute resources and receive token rewards.
* **Cross-Chain Support**: Based on BSC and supporting multi-chain interactions to break ecosystem barriers.

EveryAI's vision is to make AI capabilities ubiquitous like water and electricity - instantly accessible, truly realizing "AI for Everyone".

### **Core Innovations**

#### **（1）DePIN × AI: Revolutionary Integration of Physical Resources**

* **Idle Devices Become Computing Nodes**: Transforming the idle computing power of billions of global devices (with an average daily utilization rate of less than 5%) into AI inference resources.
* **Dynamic Resource Pool**: Using smart contracts to real-time match task requirements with device capabilities (such as GPU model, memory, network latency).
* **Chip Blockade Resistance**: Supporting heterogeneous chip hybrid computing, reducing dependence on NVIDIA GPUs.

#### **（2）AI Agent: Intelligent Intermediary Restructuring User Experience**

* **Task Automation**: Users describe needs in natural language, and Agents automatically decompose tasks, select models, and allocate resources.
* **Context Awareness**: Providing personalized services based on user historical behavior and local data (e.g., prioritizing compliant nodes for medical diagnosis).
* **Privacy Custody**: Agents manage data encryption and federated learning processes, eliminating technical complexity for users.

#### **（3）Open Source Community × Economic Model: Flywheel Ecosystem**

* **Model Marketplace**: Developers can upload open-source models (like DeepSeek, Llama 3), sharing revenue based on usage.
* **Federated Fine-Tuning**: Optimize models in encrypted environments using local user data, feeding back to the public model library.
* **Decentralized Governance**: Community decides network upgrades, resource pricing, and ecosystem fund allocation through DAO voting.