All case studies
client
FinTech AI

Trading Neural Network

Custom AI signal system for a trading desk. Pattern recognition on market data, automated technical analysis, and real-time entry/exit alerts.

2 hrs → 10 min analysis
30+ instruments
3-yr backtest
Finance / TradingSingaporeDiscuss a similar project ->
// automation architecture
Claude APItrigger
Automationorchestration
Claude APIintelligence
Telegram Botdelivery
24/7, no humans
// The problem

A trading desk spending hours on manual chart analysis every morning before markets opened. Patterns were being missed and analysis quality varied depending on who was doing it. The team needed consistent, fast signal generation across multiple assets simultaneously.

// What we built

We developed a custom neural network trained on historical price and volume data with technical indicator inputs. The model generates entry and exit signals with confidence scores. Claude processes the signals and market context into readable trade briefs. Alerts go to Telegram in real time when conditions are met, with full reasoning attached.

// Results
01Morning analysis time: 2 hours → under 10 minutes
02Coverage expanded from 5 to 30+ instruments simultaneously
03Signal consistency: no more analyst-dependent variation
04Real-time alerts on mobile with reasoning
05Backtested across 3 years of data before deployment
// Tech stack
PythonPyTorchClaude APIPostgreSQLTelegram BotCCXT
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