The Matthew K...

Thank you !

Every variable in this system — smart money flows, holder patterns, exchange movements, on-chain signals — comes from one source. I built the model. @nansen_ai built the data. If you want to see what 196 features per token looks like: nsn.ai/10x (10% off) No opinions. Just math.

Built a 3-tier composite exit scored 0-10: → Kill signals: hard cutoffs backed by zero-recovery data → Warning signals: structural decay across 7 indicators → Composite: when the math says go, you go The buy/sell ratio alone predicts ROI: • BSR 3.0+ → 100% win rate, 2,427% median • BSR < 1.0 → 34% win rate, negative median 26 variables. 3 tiers. One score. The system sees the top before you feel it.

I trained an XGBoost model on 196 features to predict which tokens pump. ~1,068 tokens scored daily. Results at 14 days: • 15 tokens, 100% win rate, 2,603% median ROI • 28 tokens, 96% win rate, 223% median ROI • 65 tokens system-wide, 91% win rate, 221% median Some catches hit 37,000%+. Then I realized — knowing WHEN to buy was only half the problem. So I analyzed 108 winners across 503 variables to find when to sell. What the data showed changed how I think about exits entirely. @nansen_ai #SmartMoney #ML

Everything in this thread runs on data from Nansen's smart money API. 1,685 tokens tracked across Solana, Ethereum, Base, BSC, and 14 more chains. 16 signals computed every 4 hours. Gate system filters down to the top 84. The API gives you raw wallet-level data: who's buying, who's selling, how much, and when. Without that underlying data - no gates. No signals. No simulator. If you want to see what smart money is actually doing: nsn.ai/10x (10% off)

The data was right. The execution was wrong. My research showed 76-100% win rates at the best gates. But translating that into buy/sell logic exposed 5 problems no research would've predicted. Stale data. Signal timing conflicts. Sensitive exits. Loose stops. Buying without conviction. Every one invisible until real trades hit the database. The simulator now runs 24/7. Auto-restarts on reboot. Scans every 4 hours. Monitors positions every 15 minutes. Every buy and sell gets a full market snapshot. When I move to real money, every rule will have been forward-tested against live data. Build the system. Test the system. Trust the system.

I caught a token at $1.27M market cap. 24 hours later it hit $3.02M. +137%. My trailing stop locked in +88% , sold at $2.39M before the crash back to $1.75M. That's $8.80 profit on a $10 paper trade. But here's the thing - I didn't risk a single dollar. This was a simulator. And if I had used real money? I would have lost on 50% of my other trades. Because the system that caught MONGO also bought 6 tokens and sold them within seconds. Bought 13 tokens with frozen price data. And triggered sells on winners too early. One great trade. Five hidden bugs. That's why you simulate first.

Every number in this thread comes from @nansen_ai smart money data. Support the research and get 10% OFF Nansen. nsn.ai/10x (10% off) #SmartMoney #NansenAPI #OnChain

What retail sees: low volume, boring market. What the pipeline sees: SM weekday activity down 20%. Not a crash. Not a panic. A measured pullback — fewer wallets, fewer tokens, but trade volume barely moved (-14%). Smart money is selective, not absent. 83 tokens still at Gate 3. 13 CRITICAL. The system watches 24/7 so you don't have to.

14 days of SM activity — every number from real wallet data: Mar 25 (Wed) → 62 wallets · 159 tokens · 517 trades Apr 1 (Wed) → 48 wallets · 124 tokens · 520 trades Apr 3 (Fri) → 36 wallets · 111 tokens · 421 trades Weekday wallets: -20% Weekday tokens: -21% Weekday trades: -14% Weekends drop to 24-29 wallets every time. Normal. Pipeline healthy. All 16 DAGs green. Signal is in the weekday trend, not weekend noise.

Smart money pulled back — but not how you think. My pipeline tracks every SM wallet trade across 12 chains. Every 4 hours. Week 1 weekday avg: 52 wallets Week 2 weekday avg: 41 wallets -20% decline. Weekday to weekday. Weekends always dip (~24-29). That's noise. The weekday signal matters. 16 DAGs. 14,500+ trades. @nansen_ai #SmartMoney #OnChain

5/ Every number in this thread comes from one place. @nansen_ai smart money data. Same API, same endpoints, same labeled wallets. /dex-trades for raw feed. /flow-intelligence for enrichment. /holders and /netflows for deep selection. You do not need my pipeline. You need the data source. Everything else can be built. Access Nansen with 10% off. Support my project, support yourself. Start building now before everyone else figures this out. nsn.ai/10x

4/ Tokens are making it into the successful filtrated gates. That part works. But getting IN is only half the problem. Getting OUT at the right time is where the real money is. This week: 1. Exit conditions. Auto-drop when pump is done, no recovery within 48h 2. Gate cleanup. Remove non-promising moves 3. Trailing stop. Protect gains above +20% with -5% stop 4. Backtest exit timing against 30 days of data When this is done the system will be fully autonomous. Entry to exit. No manual intervention. That is what keeps me going at 2am.

9,000 smart money trades per batch. Filtered down to 22 tokens a day that will pump. 80%+ win rate. Average ROI above 100%. Some hit multiple X. Others at least 50% gain. Based on data. No "trust me bro." Just data from 236 labeled wallets doing the talking. Built on @nansen_ai smart money API. #NansenAPI #onchain #smartmoney