AI-Powered Crypto Trading Bot Development
Budget: ₹12,500 – ₹37,500 INR
Product Name: SolSniperX
1. Purpose
SolSniperX is an AI-powered crypto trading bot that automatically scans, evaluates, and trades newly launched tokens on Pump.fun (Solana-based), aiming to turn $10–$30 into $50,000–$1,000,000 by executing low-risk, high-reward strategies.
2. Goals & Objectives
Objective Description
High Return Potential Identify tokens with 100x–10,000x growth and enter early
Minimized Risk Rug-proof detection and strict capital preservation
Multi-Mode Strategy Moon Strategy (High Risk–High Return) and Farm Strategy (Quick Profit)
Full Automation Run autonomously on Windows and Android (Termux)
Advanced Monitoring Live liquidity, wallet, and price behavior monitoring
3. System Features
A. Token Scanner
Scans pump.fun, Dexscreener, and Birdeye in real-time
Filters based on launch age, liquidity, price velocity
B. AI Evaluation Engine
ML model (XGBoost or LightGBM) trained on 20,000+ token launches
Predicts token’s probability of reaching 100x–10,000x
Returns confidence score (must be ≥ 99%)
C. Trading Execution
Auto-buy and sell via Phantom Wallet (Solana)
Supports:
Custom slippage (1–5%)
Multi-stage entries
Trailing stop-loss exits
Real-time TX broadcasting
D. Wallet & Liquidity Monitor
Tracks top holders (whales)
Checks dev wallet activity
Monitors LP addition/removal
Detects honeypot or anti-sell code
E. Profit Manager
Logs trades
Tracks ROI per entry stage
Sends real-time Telegram alerts
4. Two Trading Modes
Mode 1 – Moon Token Strategy
Investment: $30 (split into 3 × $10)
Stage 1: Buy at 5–10x, exit at 100x
Stage 2: Re-entry at dip, exit 40–60% at 300–800x
Stage 3: Optional entry, full exit based on momentum or stop-loss
Mode 2 – Farm Token Strategy
Investment: $5–$10
Sell 70% at 80–90x
Sell 20% at 100x
Hold 10% until ATH or 25% drop
5. Risk Management
Feature Function
Max per-token investment $30 total
Liquidity drop detection Immediate exit if >20% LP is removed
Honeypot/anti-sell detection Smart contract bytecode scanner
Trailing stop-loss Configurable (-20% from ATH default)
Kill switch Exit all open positions if 2+ red flags trigger
Wallet rotation Uses new wallet every 3 trades to avoid tracking
6. AI/ML Model Details
Attribute Description
Model Type Gradient Boosting Classifier (XGBoost)
Input Features Liquidity, holder count, top wallet %, etc.
Output 100x/300x/1000x prediction + confidence
Training Dataset 20,000+ historic Solana token launches
7. Supported Platforms
Platform Tools & Stack Used
Windows Python 3.11+, Solana-py, Phantom Wallet SDK, Streamlit
Android Termux, Phantom API, Python, Solana CLI
8. Telegram Alert System
Push Alerts For:
Token Entry/Exit
Trailing Stop-loss Trigger
Emergency Exit
Wallet movement alerts
9. Security & Privacy
Private Key Encryption: AES-256 encrypted key storage
Read-only Explorer API: For scans (Birdeye, Dexscreener)
Transaction Preview: Simulated buy/sell before execution
Wallet Isolation: Separate Phantom wallet per session
10. Performance Metrics
Metric Target
Token detection latency < 5 seconds post-deployment
Entry-execution delay < 1.5 seconds
Prediction accuracy ≥ 99% for 100x tokens
Exit speed (risk trigger) < 2 seconds
ROI 500x–10,000x per successful token
11. Testing & Simulation
Backtest AI engine with historic memecoins
Simulate 100 real trades using read-only wallet mode
Manual override toggle for expert traders
12. Deliverables
1. Complete source code (Python)
2. Windows .exe build (optional)
3. Android Termux version (.sh + Python virtualenv)
4. Telegram Bot integration
5. Configurable settings file (config.json or .env)
6. Trade log output file (profit_log.csv)
7. Model training notebook (Jupyter)
13. Timeline & Milestones
Milestone Duration
Initial Bot Code Dev 5–7 days
AI Model Training 3 days
Telegram Integration 2 days
Testing & Optimization 4 days
Final Packaging 2 days
Timeline 15-30days
14. Appendix: Tools & Libraries
Category Tools
Blockchain solana-py, anchorpy, web3
ML XGBoost, Pandas, Scikit-learn
UI Streamlit, Tauri (optional UI)
Automation asyncio, websockets, aiohttp
Mobile Dev Termux, Phantom API, Python
Alerts python-telegram-bot
1. Purpose
SolSniperX is an AI-powered crypto trading bot that automatically scans, evaluates, and trades newly launched tokens on Pump.fun (Solana-based), aiming to turn $10–$30 into $50,000–$1,000,000 by executing low-risk, high-reward strategies.
2. Goals & Objectives
Objective Description
High Return Potential Identify tokens with 100x–10,000x growth and enter early
Minimized Risk Rug-proof detection and strict capital preservation
Multi-Mode Strategy Moon Strategy (High Risk–High Return) and Farm Strategy (Quick Profit)
Full Automation Run autonomously on Windows and Android (Termux)
Advanced Monitoring Live liquidity, wallet, and price behavior monitoring
3. System Features
A. Token Scanner
Scans pump.fun, Dexscreener, and Birdeye in real-time
Filters based on launch age, liquidity, price velocity
B. AI Evaluation Engine
ML model (XGBoost or LightGBM) trained on 20,000+ token launches
Predicts token’s probability of reaching 100x–10,000x
Returns confidence score (must be ≥ 99%)
C. Trading Execution
Auto-buy and sell via Phantom Wallet (Solana)
Supports:
Custom slippage (1–5%)
Multi-stage entries
Trailing stop-loss exits
Real-time TX broadcasting
D. Wallet & Liquidity Monitor
Tracks top holders (whales)
Checks dev wallet activity
Monitors LP addition/removal
Detects honeypot or anti-sell code
E. Profit Manager
Logs trades
Tracks ROI per entry stage
Sends real-time Telegram alerts
4. Two Trading Modes
Mode 1 – Moon Token Strategy
Investment: $30 (split into 3 × $10)
Stage 1: Buy at 5–10x, exit at 100x
Stage 2: Re-entry at dip, exit 40–60% at 300–800x
Stage 3: Optional entry, full exit based on momentum or stop-loss
Mode 2 – Farm Token Strategy
Investment: $5–$10
Sell 70% at 80–90x
Sell 20% at 100x
Hold 10% until ATH or 25% drop
5. Risk Management
Feature Function
Max per-token investment $30 total
Liquidity drop detection Immediate exit if >20% LP is removed
Honeypot/anti-sell detection Smart contract bytecode scanner
Trailing stop-loss Configurable (-20% from ATH default)
Kill switch Exit all open positions if 2+ red flags trigger
Wallet rotation Uses new wallet every 3 trades to avoid tracking
6. AI/ML Model Details
Attribute Description
Model Type Gradient Boosting Classifier (XGBoost)
Input Features Liquidity, holder count, top wallet %, etc.
Output 100x/300x/1000x prediction + confidence
Training Dataset 20,000+ historic Solana token launches
7. Supported Platforms
Platform Tools & Stack Used
Windows Python 3.11+, Solana-py, Phantom Wallet SDK, Streamlit
Android Termux, Phantom API, Python, Solana CLI
8. Telegram Alert System
Push Alerts For:
Token Entry/Exit
Trailing Stop-loss Trigger
Emergency Exit
Wallet movement alerts
9. Security & Privacy
Private Key Encryption: AES-256 encrypted key storage
Read-only Explorer API: For scans (Birdeye, Dexscreener)
Transaction Preview: Simulated buy/sell before execution
Wallet Isolation: Separate Phantom wallet per session
10. Performance Metrics
Metric Target
Token detection latency < 5 seconds post-deployment
Entry-execution delay < 1.5 seconds
Prediction accuracy ≥ 99% for 100x tokens
Exit speed (risk trigger) < 2 seconds
ROI 500x–10,000x per successful token
11. Testing & Simulation
Backtest AI engine with historic memecoins
Simulate 100 real trades using read-only wallet mode
Manual override toggle for expert traders
12. Deliverables
1. Complete source code (Python)
2. Windows .exe build (optional)
3. Android Termux version (.sh + Python virtualenv)
4. Telegram Bot integration
5. Configurable settings file (config.json or .env)
6. Trade log output file (profit_log.csv)
7. Model training notebook (Jupyter)
13. Timeline & Milestones
Milestone Duration
Initial Bot Code Dev 5–7 days
AI Model Training 3 days
Telegram Integration 2 days
Testing & Optimization 4 days
Final Packaging 2 days
Timeline 15-30days
14. Appendix: Tools & Libraries
Category Tools
Blockchain solana-py, anchorpy, web3
ML XGBoost, Pandas, Scikit-learn
UI Streamlit, Tauri (optional UI)
Automation asyncio, websockets, aiohttp
Mobile Dev Termux, Phantom API, Python
Alerts python-telegram-bot