> For the complete documentation index, see [llms.txt](https://evoai.gitbook.io/evoai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://evoai.gitbook.io/evoai/2.technology-and-architecture/editor.md).

# Core Components

#### BNB Chain Layer

Role: Provides a high-performance blockchain for transparent governance, token transactions, and smart contract execution. 

#### Advantages:

1. Scalability: Supports 5,000+ transactions per second (TPS). 
2.  Low Cost: Average transaction fee of $0.01. 
3.  Interoperability: Compatible with Ethereum Virtual Machine (EVM), enabling seamless
   \
   integration with existing DeFi and Web3 ecosystems.

#### DeepSeek AI Framework

Role: A state-of-the-art AI engine optimized for distributed training and inference. 

Features:

1. Federated Learning: Enables privacy-preserving model training across decentralized nodes. 
2. Adaptive Resource Allocation: Dynamically distributes computational resources based on
   \
   demand. 
3. Cross-Model Interoperability: Facilitates collaboration between AI agents. 

#### AI Agent Marketplace

Role: A decentralized platform for developers to launch, monetize, and share AI agents.  

Use Cases:

1. DeFi Trading Bots: Automate trading strategies with real-time market analysis. 
2.  NLP Chatbots: Provide customer support and engagement. 
3.  Predictive Analytics: Optimize supply chains and logistics. 

#### Data Oracles and Privacy

Role: Secure data acquisition through decentralized oracles. 

1. Zero-Knowledge Proofs (ZKPs): Ensure privacy-preserving data usage. 
2.  Decentralized Storage: Leverage IPFS and Filecoin for secure data storage.