DeFi Seer leverages AI-powered agents and G.A.M.E SDK to revolutionize decentralized finance by providing real-time insights, predictions, and investment strategies.
- AI-Driven Insights: Predict token trends, liquidity movements, and market shifts.
- Custom Strategies: Tailored investment plans based on risk profiles.
- Seamless Integration: Supports major DeFi protocols like Uniswap, Aave, and Curve.
- Clone the repository:
git clone https://github.com/your-username/defi-seer.git cd defi-seer
defi-seer/
│
├── README.md # Overview of the project (intro and quick links)
├── whitepaper/
│ ├── whitepaper.md # Full whitepaper content (Markdown format)
│ └── references.md # References section from the whitepaper
│
├── docs/ # Documentation for developers and contributors
│ ├── introduction.md # Overview of DeFi Seer
│ ├── architecture.md # Technical architecture details
│ ├── api-reference.md # API documentation for developers
│ ├── integration-guides/ # Guides for integrating with specific protocols
│ │ ├── uniswap.md
│ │ ├── aave.md
│ │ └── curve.md
│ └── faq.md # Frequently Asked Questions
│
├── contracts/ # Smart contract code
│ ├── audits/ # Audit reports for smart contracts
│ │ ├── initial-audit.pdf
│ │ └── re-audit.pdf
│ ├── Token.sol # $DS token smart contract
│ ├── Staking.sol # Staking functionality contract
│ └── Governance.sol # Governance smart contract
│
├── ai/ # AI agent code and models
│ ├── trend-prediction/ # Trend prediction model code
│ │ ├── model.py
│ │ └── dataset.csv
│ ├── risk-management/ # Risk management algorithm
│ │ ├── model.py
│ │ └── utils.py
│ └── strategy-optimizer/ # Investment strategy optimization code
│ ├── optimizer.py
│ └── config.json
│
├── sdk/ # SDK for integrating DeFi Seer
│ ├── installation.md # Installation guide for the SDK
│ ├── usage-examples.md # Examples of how to use the SDK
│ └── sdk.js # Main SDK code (JavaScript/TypeScript example)
│
├── ui/ # User Interface code for the platform
│ ├── src/
│ │ ├── components/ # React/Vue components
│ │ ├── pages/ # Main pages (e.g., dashboard, analytics)
│ │ └── utils/ # Utility functions
│ ├── public/ # Static assets (e.g., images, icons)
│ └── package.json # Frontend dependencies
│
├── tests/ # Test cases for the project
│ ├── unit-tests/ # Unit tests for contracts and AI code
│ ├── integration-tests/ # Integration tests for the SDK and UI
│ └── test-config.json # Test configuration file
│
├── scripts/ # Deployment and automation scripts
│ ├── deploy.sh # Deployment script for contracts
│ ├── data-prep.py # Data preparation for AI models
│ └── monitoring.py # Monitoring script for live systems
│
├── LICENSE # License for the project
└── CONTRIBUTING.md # Contribution guidelines
- Explore the documentation in the
docs/directory for integration and usage.
whitepaper/: Full whitepaper and references.contracts/: Smart contracts for $DS token, staking, and governance.ai/: AI models for predictions, risk management, and strategy optimization.sdk/: SDK for integrating DeFi Seer into other applications.ui/: Source code for the user interface.tests/: Unit and integration tests.scripts/: Deployment and automation scripts.
We welcome contributions! Please refer to the CONTRIBUTING.md file for guidelines.
This project is licensed under the terms of the MIT License.
Empowering investors with AI-driven insights to navigate the DeFi ecosystem confidently.
To revolutionize decentralized finance by providing real-time predictions, actionable insights, and tailored investment strategies.
- Executive Summary
- Key Value Proposition
- Product Details
- Roadmap
- Token Utility ($DS)
- Team
- Conclusion
- References
Explore the full whitepaper online
-
G.A.M.E SDK Documentation
https://whitepaper.virtuals.io/developer-documents/game-framework -
DeFi Market Overview
https://defipulse.com/ -
Uniswap Protocol Documentation
https://docs.uniswap.org/ -
Aave Protocol Documentation
https://docs.aave.com/ -
Curve Finance Resources
https://curve.fi/ -
Smart Contract Auditing Standards
https://consensys.net/diligence/ -
AI Ethics in Fintech
https://www.weforum.org/ This project is licensed under the terms of the MIT License.