maiga
  • Intro to Maiga.ai
    • Maiga litepaper
  • Maiga Intro
    • 🤖What is Maiga.ai?
    • ❓Why Maiga.ai?
    • ⏳Market gap
    • 🦸Use case
  • Maiga Tech
    • 🦾AI Agent
    • 👷How it works?
      • Features
      • Examples
      • 🆚Comparison
    • 🦿Technology
      • Architecture
      • Key Elements
      • LLMs
      • 👻Abstraction
    • 🚀Launchpad
    • 🚆Roadmap
  • MAIGA token
    • 🙌Introduction
      • PoT whitepaper link
    • 🍯“Proof of Trading”
      • Math formula
    • 🗝️Option token
    • ℹ️Token utility
    • 🚀Tokenomics
    • 🥧Allocation
    • 🎰Game Theory 3,3
    • 🤑Incentives
    • 🦄Public sale & IDO
  • Incentives
    • 🤑Boost XP
      • 🎁Reward Hash
      • ➡️How to Boost XP?
      • FAQ
    • 🚀Pre-TGE campaign
  • Maiga links
    • 🔗Official links
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On this page
  • Agent Operating System
  • Data Integration and Processing
  • DeFAI Integration
  • Tokenomics and Economic Models
  • Relevant GitHub Repositories
  1. Maiga Tech
  2. Technology

Key Elements

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Last updated 3 months ago

Agent Operating System

ElizaOS: Maiga.ai will be built on top of ElizaOS, an open‑source framework for autonomous agents. This provides core features such as multi-agent support, memory retrieval, document ingestion, and customizable “character” configurations.

Data Integration and Processing

Maiga.ai will incorporate multiple data streams to inform its trading and decision‐making:

Crypto Funding Rates: Ingest data from exchanges (e.g., Binance, Bybit, Coinbase, OKX).

Sentiment Analysis: Use natural language processing (NLP) on Twitter, Telegram, and other social media data (potentially leveraging APIs like LunarCRUSH).

Exchange Orderflow: Interface with exchanges via standardized libraries (e.g., ) to analyze order book data.

Whale Wallet Tracking: Integrate with blockchain explorers (e.g., Etherscan API, Whale Alert) to monitor large wallet activities.

A dedicated data layer will pre‑process, filter, and merge these inputs using machine learning algorithms (implemented in Python) so that the AI agent can react to market conditions.

DeFAI Integration

AUTOMATE by HeyAnonAI: Maiga.ai will integrate with complementary DeFAI frameworks such as AUTOMATE to streamline task automation on multiple DeFi dapps integration.

ThirdFi API

ThirdFi API: Maiga.ai will be using several APIs developed by ThirdFi such as on-off fiat-crypto ramps and crypto trading signals as data integration and processing.

Tokenomics and Economic Models

Bonding Curve Model:

To launch and scale the AI agent’s token economy, Maiga.ai will use a bonding curve mechanism similar to that popularized by Virtuals.io. This model sets the token price as a function of supply (with early buyers receiving a discount and later buyers paying a premium).

Proof of Trading (PoT) Integration:

Maiga.ai’s native token model is based on “Proof of Trading” (PoT) that rewards active trading volume and liquidity rather than linear vesting. This ensures fairer distribution and incentivizes market participation.

Relevant GitHub Repositories

Below is a list of the core repositories (with verified, original URLs) that form part of the Maiga.ai development ecosystem:

ElizaOS (Autonomous Agent Operating System):  •  – Provides the foundational framework for building AI agents.

ElizaOS Starter Template:  •  – A template for quickly bootstrapping an agent project.

ElizaOS Characterfile (for defining agent personalities):  •

AUTOMATE Framework by HeyAnonAI (for DeFAI integration):  •

Maiga.ai Proof of Trading Documentation:  •  •

Virtuals Protocol Whitepaper (Reference for bonding curve economics):  •

🦿
ElizaOS GitHub repo
CCXT
AUTOMATE Framework GitHub repo
ThirdFi API documentation
Maiga.ai Bonding Curve Auto-Launchpads for AI Agents
Maiga.ai Proof of Trading Page
Maiga PoT Documentation on GitBook
https://github.com/elizaOS/eliza
https://github.com/elizaOS/eliza-starter
https://github.com/elizaOS/characterfile
https://github.com/RealWagmi/anon-integration-guide
https://www.maiga.ai/proof-of-trading
Maiga PoT on GitBook
https://whitepaper.virtuals.io/