Unibase Docs
  • Introduction
    • Architecture
    • Core Components
    • Quick Start
  • Membase
    • 📚Architecture
    • Identity
    • Multi Memory
    • Authorization
    • 🚀Quick Start
  • AIP
    • Design
    • Agent Interaction Process
    • Implementation
    • Quick Start
      • Tool
      • Agent
        • Agent-Tool Interaction Via gRPC
        • Agent-Tool Interaction Via SSE
        • Agent-Agent Interaction
      • Chess game
  • Unibase DA
    • DA
    • Storage
    • Quick Start
      • Nodes boostrap
        • Storage Node
        • Validator Node
        • Stream Node
        • Docker
      • Nodes operations
  • Developers
    • Hub
    • SDK
    • API Reference
  • Alpha Testing
    • Testing plan
    • Requirements
    • Chains
  • 🚀Examples
  • AIP Whitepaper
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On this page
  • 1. What is Unibase?
  • 2. Project Status
  • 3. Problems Solved
  • 4. Core Modules
  • 5. Ecosystem Projects

Introduction

1. What is Unibase?

Unibase is the first high-performance decentralized AI memory layer. It equips AI agents with long-term memory and cross-platform interoperability, enabling them to learn, evolve, and collaborate autonomously.

Unibase is building the foundation for the Open Agent Internet — a modular, verifiable, and composable AI agent ecosystem onchain.

2. Project Status

  • ✅ Testnet Live on BNBChain Testnet

  • ✅ SDKs, Docs, and Explorer fully released

  • ✅ Integrated with MCP, ElizaOS, Virtuals, and Swarms

  • ✅ 1,000+ agent interactions recorded via Unibase SDK

  • ✅ BitAgent, TradingFlow, TwinX, Beeper online

3. Problems Solved

  • No Long-Term Memory - Traditional AI agents fail to retain continuous, long-term context, limiting their ability to learn and personalize interactions.

  • Lack of Interoperability - AI agents are isolated within specific ecosystems, making knowledge sharing and collaboration across platforms difficult.

  • Data Sovereignty Issues - Centralized data systems risk privacy and transparency for users, limiting trust in AI-driven services.

4. Core Modules

  • Membase: Decentralized memory layer, providing secure, scalable long-term memory for AI agents.

  • AIP Protocol: Web3-native agent interoperability protocol, enabling agents to communicate and share knowledge across platforms.

  • Unibase DA — High-performance data availability layer that enables secure, real-time data retrieval and storage with low latency and high throughput.

5. Ecosystem Projects

  • 🤖 BitAgent — Multi-agent platform for agent deployment, coordination, and DAO-based governance

  • ✨ TwinX — Self-evolving agent builder from social media content

  • 📈 TradingFlow — AI-native agent system for autonomous DeFi strategies

  • 🧠 Integrated with frameworks: MCP, ElizaOS, Virtuals, Swarms

📌 Summary

Unibase solves the missing memory and interoperability layer for decentralized AI. By enabling verifiable, composable, and persistent agent infrastructure onchain, Unibase turns any EVM chain into AI-native — laying the groundwork for a future where autonomous agents operate across ecosystems, with full transparency and evolution.

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Last updated 23 hours ago