DeepAgents has a modular design with a framework that supports deep user customization for specific analytical needs. The core of the system provides standard analytical processes and underlying tools, while opening up several extension interfaces that allow professional users to add new analytical dimensions or adapt existing models.
Key scalability points include:
- Data Source Extension:Default integration with yfinance library for U.S. stock data acquisition, users can write adapters to interface with A-share, Hong Kong stock or other proprietary data sources.
- Subintelligentsia Extension:Support the addition of new specialized analyst roles such as ESG Analyst (Environmental, Social and Governance Assessment), Sector Analyst or Macro Strategist
- Analytical Model Extensions:Allows import of customized technical indicator calculation models, valuation models or risk assessment frameworks
A typical extension case is to add support for the A-share market: first, a data acquisition module is written to interface with Chinese data sources, then the analysis logic is adapted to A-share-specific trading rules and accounting standards, and finally a language model optimized for Chinese financial terminology may need to be trained.
This scalability allows DeepAgents to be used not only for personal investment research, but also through secondary development to meet the specific needs of professional users such as private equity funds and research organizations. The development team recommends that users start with the basic functionality to familiarize themselves with the system architecture, and then proceed step by step with custom development.
This answer comes from the articleDeepAgents: an AI Intelligence for Professional-Grade Equity ResearchThe
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