I've been experimenting with the idea of connecting TradingView alerts to an AI decision layer to make trading more systematic. The architecture is relatively simple: TradingView TradingView generates a signal when predefined conditions are...
I've been experimenting with the idea of connecting TradingView alerts to an AI decision layer to make trading more systematic.
The architecture is relatively simple:
TradingView
↓
Webhook
↓
Trading Signal API
↓
Claude / AI Analysis
↓
Risk Management
↓
Broker API
TradingView generates a signal when predefined conditions are met—for example, an EMA crossover, VWAP confirmation, RSI threshold, or volume breakout.
The webhook sends structured JSON to an application:
{
"symbol": "NVDA",
"signal": "LONG",
"timeframe": "5m",
"price": 182.50
}
The application can then send the relevant market data to an AI model for structured analysis.
The AI shouldn't have unrestricted control over trading.
A separate risk-management layer should enforce position size, stop-loss, maximum daily loss, and other limits before anything reaches the broker.
The interesting part isn't trying to make AI predict the market.
It's using automation to create a repeatable process that reduces emotional decisions.
Before connecting real capital, the entire pipeline should be backtested, paper traded, monitored, and tested for failure scenarios.
Good automation doesn't eliminate risk. It makes risk more visible and controllable.
-- Dipendra Shrestha | Virginia