SignalFlow Agent — AI Trading Signal Dashboard
AI trading signal dashboard — 5-Layer Signal Engine V2, multi-timeframe confluence, paper futures trading. SoSoValue Buildathon 2026 submission.
Context
A custom build where the business flow mattered more than plugging in a generic template.
Project at a glance
SignalFlow Agent mengubah multi-dimensional market data menjadi trade signals yang explainable. Problem: trader retail butuh sistem yang bisa analisis multi-factor (trend, momentum, volatility, volume, structure) secara otomatis dan execute paper trades — bukan cuma chart viewer. Solution: 5-Layer Signal Engine V2 dengan market regime detection, 7-tier classification, dan wallet-aware paper futures validation. Bloomberg-style command center dengan pipeline visualization.
What this case helps prove
The challenge
Trader retail kesulitan mengintegrasikan data dari banyak sumber (ETF flows, sentiment, macro events, technical indicators) menjadi satu keputusan trading yang koheren. Platform existing hanya chart viewer tanpa signal classification atau automated execution.
The response
5-Layer Signal Engine V2 yang menggabungkan Trend, Momentum, Volatility, Volume, dan Structure analysis dengan market regime detection. Setiap signal dianalisis di 3 timeframe (1H, 4H, 1D) dengan alignment scoring. Paper futures trading dengan virtual USDC, auto TP/SL/liquidation, dan per-type performance stats.
Why it mattered
SoSoValue Buildathon 2026 submission by NoHype Labs
Before and after, in clearer terms
The point of this section is not decoration. It is to show the operational shift in terms the client team can immediately recognize.
Signal analysis
Before
Manual cek 5+ indikator di berbagai platform
After
Auto 5-factor confluence + 3-timeframe alignment
Trade execution
Before
Manual open/close, rawan emosi
After
Paper futures dengan auto TP/SL/liquidation
Performance tracking
Before
Tidak ada atau manual spreadsheet
After
Per-type stats: Sharpe, Sortino, Calmar, drawdown
Key highlights of the build
5-Layer Signal Engine V2
Multi-factor confluence system: Trend, Momentum, Volatility, Volume, Structure — dengan market regime detection, 7-tier classification, dan volatility-adjusted TP/SL. Adaptif ke 4 trading styles (Scalper, Intraday, Swing, Position)
Multi-Timeframe Confluence
Setiap signal dianalisis independent di 3 timeframe (1H, 4H, 1D) dengan alignment scoring. Semua 3 timeframe agree = 95 conviction score, conflicting = 30-50
End-to-End Signal-to-Execution
Bloomberg-style command center dengan pipeline visualization. Paper futures trading dengan virtual USDC, auto TP/SL/liquidation, leverage 1x-100x, dan per-type performance stats
Impact that stayed visible
What the system includes
Technology stack
Frontend
Backend & Database
Integrations
Architecture
If this kind of operational shift is what you need, start from the problem.
The fastest useful next step is not asking for a random feature list. It is clarifying what feels weak today, what friction the team still carries, and what a cleaner first version should solve.