AI Core
The AI Core is the heart of the Fimain protocol. It is a neural decision engine that autonomously manages liquidity, optimizes yield, and ensures stable, predictable rewards for all participants.
1. Model Architecture
Fimain integrates over 100 independent ML/AI models operating in dynamic consensus.
Each model evaluates market conditions, liquidity flows, and volatility to generate actionable insights.
Models work together to reallocate capital, predict profitable opportunities, and minimize exposure to risk.
The architecture is modular, allowing new models to be added without disrupting the system.
2. Consensus Mechanism
Decisions are made via aggregated voting and weighted signals from all active models.
Each model contributes based on its confidence and historical performance.
The consensus ensures that capital allocation is data-driven and risk-aware, reducing errors from any single model.
This approach creates a robust, self-correcting AI system capable of operating in volatile markets.
3. Model Types
Fimain AI leverages a diverse set of models, including:
Time-Series Predictors — forecast price trends and market cycles.
Reinforcement Learning Agents — learn optimal allocation strategies through continuous simulation.
Arbitrage Detectors — identify profitable discrepancies between exchanges.
Liquidity Evaluators — monitor pool health and optimize fund distribution.
4. Data Inputs
The AI Core uses both on-chain and off-chain data to make accurate decisions:
On-Chain: liquidity pools, volumes, token transfers, staking activity
Off-Chain: order books, trading volumes, CEX data, macroeconomic indicators
Oracles verify external data to ensure integrity and reliability.
5. Continuous Learning
Models retrain using historical and live trading data to improve prediction accuracy.
The system adapts dynamically to new market conditions, ensuring long-term effectiveness.
Metadata and logs are stored for auditability and transparency, enabling participants to verify AI decisions.
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