68% weekly active usage
Custom Radar
Personal filters by chain, source, market cap, and holder count — with AI-suggested presets based on past trading behaviour. 68% of users set up a radar in week one.
Shipped
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Web3 · Trading Terminal · AI Driven
Trady — Trading Terminal
Designed a cross-chain meme token terminal from scratch — from auth to signal filtering to multi-wallet execution. DAU grew 40% within 6 weeks of launch.
Context
Overview & Goals
Meme coin traders operate in chaos — hundreds of new tokens per hour, social signals scattered across Telegram and X, and execution windows measured in seconds. Trady is a cross-chain terminal built for this exact environment: discover tokens, read KOL signals, filter noise, and trade — all in one place.
The problem was signal-to-noise: existing tools showed everything and filtered nothing. We used AI at the core — token ranking, KOL activity detection, and radar suggestions are all model-driven. Let AI handle the noise, traders handle the trades.
Goal
Reduce time to executed trade
Target
Active traders week over week
Design Principle
Speed as a Design Constraint
Core constraint
Designed around execution speed
The core design principle: a trader should never have to leave the terminal to act on a signal. Quick Buy & Sell buttons are persistent across every view. Token info — market cap, liquidity, TXNs, holder % — surfaces inline. Social links — Telegram, Twitter — open as tooltips on hover, not new tabs. The entire information architecture was built to keep traders in flow state. Under the hood, AI ranks incoming tokens by momentum score before they surface in Trending — traders see signal, not raw feed.
Trade in <10s
Every interaction was benchmarked against a 10-second window from token discovery to buy execution.
0 context-switching
KOL feed, radar filters, wallet selector, and quick actions live in the same viewport — no tab-switching, no drill-down.
Density by default
Information hierarchy tuned for power users: all critical data visible without scrolling. Progressive disclosure only for non-critical details.
Persistent controls
Buy / Sell buttons, wallet selector, and chain switcher are fixed in the layout — they follow the trader, not the content.
Process
What I Designed
2nd most-used tab after Trending
KOL Alpha Tab
AI tracks KOL wallet activity across chains in real time and surfaces which tokens they're accumulating — displayed as avatar stacks inline. No tab-switching to validate a signal.
Shipped
Used by 45% of active traders
Multi-Wallet Settings
Power users run multiple wallets to split buys and avoid detection. Designed Buy Variance slider, TX Delay control, Auto-Cover Shortfall toggle, and Sell Deduction Order — complex logic made scannable in a single modal.
Shipped87% registration completion rate
Auth — Sign Up & OTP
3-step flow: email → referral code (optional) → OTP verify. Google, X, and Telegram as social auth. Referral built into registration to support growth loops from day one.
Shipped
Dead ends
What We Killed
Drop 1
Social Feed
Traders liked the idea. In practice, it pulled focus away from the token list at the worst possible moment. Killed before hi-fi.
Killed before hi-fi
Drop 2
Notifications
Users asked for it. But the volume needed to be useful would've been overwhelming. A wrong alert at 3am is worse than no alert. Shelved.
Shelved — pending v2
Drop 3
Portfolio Page
Designed a full PnL analytics view. User interviews revealed traders didn't want to reflect — they wanted to act. Shipped a balance widget in the dropdown instead. Portfolio flagged for v2.
Shelved — pending v2Validation
Metrics & Evidence
First 6 weeks post-launch
DAU tracking, session recordings, and user interviews with 12 active meme traders. Benchmarks sourced from competitor session data and onboarding analytics.
Reduction in
−55%
Time from token discovery to executed trade vs. competitor baseline
Completion rate
87%
Registration completion — referral + social auth reduced drop-off
Conclusions
Results
+40%
DAU growth in 6 weeks
−55%
Time to first trade
3.2×
Session length vs. benchmark
68%
Custom Radar weekly users
Outcome
Effect
+40% DAU in 6 weeks. The terminal retained traders because it eliminated context-switching — KOL signals, custom filters, and one-click execution all in one place. Custom Radar became the stickiest feature with 68% weekly active usage. Speed wasn't a feature — it was the product. And AI was the infrastructure that made speed possible at scale.