Signalibrium
AI-assisted trading intelligence concept
Role
Solo — product design, dashboard UI, frontend development
Stack
Overview
Signalibrium is a trading intelligence platform concept focused on reducing cognitive load for active traders. Most trading tools try to show everything — news, signals, charts, positions, P&L — simultaneously. Signalibrium is built around the opposite philosophy: surface the right signal at the right time, and get out of the way.
The challenge
Active traders are chronically over-informed and under-supported. The challenge wasn't building another dashboard that shows more data — it was designing a system that helps traders make better decisions with less noise. That required rethinking what information should be visible at each stage of a trading decision.
Approach
- 01
Started with user research into how traders actually make decisions — not the idealised version, but the real process including emotional state, time pressure, and cognitive bias.
- 02
Built the information architecture around a three-stage flow: signal discovery → risk evaluation → decision and journaling.
- 03
Designed the UI to actively de-emphasise real-time price movement (which drives impulsive decisions) while emphasising risk-adjusted context.
- 04
Used a dark, focused aesthetic deliberately — to reduce visual stimulation and encourage slower, more deliberate decision-making.
Key features
Signal feed
A curated, prioritised feed of trading signals with confidence scores and context — not a raw data dump.
Risk analysis
Automatic risk/reward calculation, position sizing tools, and portfolio exposure warnings before any trade is journaled.
Trade journaling
Structured journaling built into the trade flow, not bolted on afterwards. Captures the reasoning at decision time, not retrospectively.
Decision support
Prompts and checklists that surface relevant information at the right moment — helping traders avoid common cognitive traps.
Outcome
Signalibrium is live as a UI concept and design system. The product design phase is complete. The next phase is connecting live data sources and building out the backend for signal ingestion and portfolio tracking.
Next project
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