➡️Solution Architecture (Technical Deep Dive)

WhiteList Zone is a hybrid swarm of AI agents that combines Web3 and ML:

Data Layer 🔹 AI Scrapers ×10 – Scrape from 10+ sources: Discord, X (Twitter), OTC platforms, Alphabot, Subber, Atlas3, Premint. – Update speed: every 15 minutes (6× faster than manual methods).

🔹 Swarm Agents – 12 autonomous models: → NLP classifiers for finding WL in 10 languages. → GNN (Graph Neural Networks) analysis to detect connections between projects and scam schemes. – RAG (Retrieval-Augmented Generation): real-time data updates via distributed GPUs (ElizaOS).

AI Layer 🔹 Scam Detection Engine – Analyzes 50+ parameters: from GitHub activity to tokenomics. – Outcome: filters out 80% of risks by identifying scam patterns.

🔹 PNL Predictor – Forecasts ROI using an LSTM model with a target accuracy of 80% (trained on historical public IDO data from 2021–2023).

🔹 Dynamic Pricing Core – An algorithm that adjusts the NFT box price daily based on: → Project’s social activity (Sentiment Analysis). → OTC demand (Whales Market, Exsaverse, Telegram OTC).

Execution Layer 🔹 NFT Boxes (ERC-1155) – Execution guaranteed by smart contracts (integrated with Chainlink Oracle). – Example: WL of project X sold for 0.5 ETH → 3 secondary market deals within 24 hours (+20% in price).

Visualization: An architecture diagram (3 blocks: Data → AI → Execution) with arrows: – Data Sources → AI Scrapers → Swarm Agents → PNL Predictor → NFT Boxes → Marketplace. – Captions: “Every WL goes through 4 stages of AI verification.” “Effect for projects (modeling): – CAC: reduced by 60% ($200 → $80) – Conversion: 90% of slots go to real users.”

Case Study in the corner of the slide: – “How it worked for project X: CAC reduced by 60% → $200→$80, 90% of slots purchased by real users.”

Tech stack (in small font at the bottom): ElizaOS, Chainlink, GNN, ERC-1155, LSTM.