➡️AI Swarm Agents

🤖 Multi-agent AI System:

• 🔹 Automatic data collection from 10+ sources (Twitter, Discord, GitHub, Alphabot, Subber, Atlas3, Premint, OTC)

• 🔹 Automatic collection of DM offer data from 40+ partner launchpads

• 🔹 On-chain data analysis (TVL, FDV, holders, GitHub)

• 🔹 Social scoring analysis (Moni Score, Tweetscout, mentions on CT Crypto Twitter, engagement analysis and proof of community verification of real users (fake engagement detection), ratio of online users to total users, fake users, low-score users, off-topic chat messages)

• 🔹 Trend tracking (AI, DeFi, DePIN, NFT PFP)

• 🔹 Automatic submission of whitelist applications

⚡ Technologies:

• ✅ NLP models (social network analysis, sentiment, BERT, DeepSeek r1, GPT-4o)

• ✅ Graph Neural Networks (on-chain activity analysis using PyTorch Geometric)

• ✅ Federated Learning for data protection (self-learning AI agents)

Training Stages for the Agents:

• 🔹 Stage 1: Collection of historical data (2021–2024) → 100k+ WL events.

• 🔹 Stage 2: Training NLP models to recognize scam patterns (RoBERTa, DeepSeek).

• 🔹 Stage 3: Testing agents in simulation → 79% accuracy on the test sample.

Example: A project launches a giveaway → the AI agent parses the data → applies multi-accounting → adds whitelists to the marketplace within minutes.