Trading is complex: data collection, signal analysis, risk management, execution, settlement.
Each step involves different tools, agents, and humans. Without orchestration, chaos.
TradeFlow solves this with UiPath Maestro Case. The pipeline runs as a structured case:
1. INTAKE — Market Agent pulls real-time data from Binance
2. ANALYSIS — Python LangChain agent computes RSI/MACD signals
3. DECISION — Risk Agent evaluates every trade against portfolio limits. High-risk trades trigger human-in-the-loop approval via Slack notification.
4. EXECUTION — Approved trades execute automatically via Binance API
5. SETTLEMENT — Trade history logged, portfolio updated
Built with:
- Python LangChain agents for analysis and execution
- UiPath Maestro Case as the orchestration layer
- Binance API for real-time market data
- Human-in-the-loop via UiPath's approval workflows
The key innovation: UiPath doesn't just run automation — it governs AI agents at scale.
TradeFlow shows how agentic trading works in production, not just on a laptop.
Demo output: tradeflow_demo.json shows a complete pipeline trace from market scan to executed trades.
TradeFlow
AI-driven trading pipeline that orchestrates market analysis, risk assessment, and trade execution through UiPath Maestro Case — with human-in-the-loop checkpoints for every decision.
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