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Private Financial Data Hub

Finance data work cannot start from tool names only. Selection depends on data sources, compliance, research workflows, localization, and AI retrieval needs.

[ FINTECH ]

Private Financial Data Hub

Private deployment and customization of open-source finance tools

Scenario Case

Finance data work cannot start from tool names only. Selection depends on data sources, compliance, research workflows, localization, and AI retrieval needs.

Component Selection

OpenBBFinancial data terminal and analysis entry
QlibAI quant research and strategy experiments
AKShare / TushareLocal market data providers
RAGFlowReport knowledge base and natural language retrieval

Decision Boundaries

  • Research, quant, live trading, and report retrieval need different architectures.
  • Verify local providers, permissions, stability, and refresh cadence.
  • Treat persistence, backup, audit, and upgrades as core boundaries.
01

Selection review

Choose bases around research, quant, trading, or report retrieval.

02

Private deployment

Handle Python dependencies, persistence, containers, and intranet access.

03

Data integration

Connect AKShare, Tushare, and filing data.

04

AI enhancement

Add report retrieval, natural language querying, and sentiment analysis.

Keep core data private.
Search local market data and local-language reports.
Lower terminal and customization cost through open-source tools.
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