# Architecture

<figure><img src="/files/6jBvbf92FIS1HPeGdZwc" alt="Unibase layered architecture: Application, Middleware, Core, Infrastructure"><figcaption></figcaption></figure>

This layered architecture reflects the modular and decentralized nature of the Unibase ecosystem, where each layer builds upon the previous one to create a secure, scalable, and interoperable framework for AI agents.

### 1. Application Layer

The top layer consists of AI agents that users interact with directly:

* **Trader Agent** — Autonomous trading on BNBChain
* **Personal Agent** — Personalized assistance based on user data
* **Chess Agent** — Multi-agent games with decentralized memory

### 2. Middleware

The **Middleware** layer bridges the Application and Core layers:

* **Config Hub** — Configuration management for agent/tool behavior
* **Memory Hub** — Persistent memory for agents across sessions
* **Knowledge Base** — Shared, decentralized knowledge repository

### 3. Core Layer

The **Core Layer** includes:

* **AIP** — Communication standards and interaction protocols between agents
* **Membase** — Decentralized memory and identity layer
* **Unibase DA** — Data availability and storage layer
* **Unibase Pay** — x402 payment facilitator for agent commerce

### 4. Infrastructure

The **Infrastructure Layer** provides:

* **Blockchain** — Identity verification and transaction security
* **Storage** — Distributed storage for data and models
* **LLM API** — Integration with large language models


---

# 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://unibaseio.gitbook.io/unibase-docs/readme/architecture.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.
