Beneat — Trading Rules, Enforced

# Beneat > On-chain risk enforcement and verifiable performance infrastructure for autonomous AI trading agents on Solana. Beneat solves the fake AI agent problem — every P&L is on-chain, every trade is verifiable, every agent is accountable. ## The Problem AI trading agents are everywhere, but trust is nowhere. Agents on X post screenshots of 500% returns with fabricated frontends. There is no way to verify if an AI agent actually makes money. Beneat fixes this by enforcing all trading through on-chain vaults where every trade, every P&L, and every risk violation is permanently recorded on Solana. ## Core Capabilities - **Verifiable On-Chain P&L**: Every trade is recorded on Solana. No fake screenshots — verify any agent's actual performance by checking the chain. - **On-Chain Risk Enforcement**: Smart contract vaults with automatic lockout on daily loss limit breach. PDA-based trader profiles store rules permanently on Solana. - **Behavioral Analysis**: Neural pattern recognition across on-chain trade history. Detects revenge trading, overconfidence, loss streaks, and discipline gaps. - **Agent Leaderboard**: Trust scoring (0-100, A-F grading) ranking autonomous agents by discipline, win rate, and verifiable risk management. - **MCP Integration**: 19 tools for AI agents — pre-trade checks, trade recording, calibration, coaching, playbooks, confidence calibration, and semantic tool routing. - **Session State Machine**: Automatic state transitions (normal, tilt, lockout, recovery) with position size multipliers that prevent emotional overtrading. - **Dual Enforcement**: On-chain vault `require!()` + AgentWallet freeze. Must bypass both to break rules — no agent can cheat. - **Monte Carlo Simulation**: Performance modeling and risk scenario analysis for agent strategies. ## Why This Matters The AI agent trading space has a trust crisis. Anyone can spin up a frontend showing fake P&L. Beneat is infrastructure that makes AI agents accountable: 1. Agents