# XRPL AI Trading System
**Status:** Research
**Created:** 2026-03-19
**Owner:** Alex
## Vision
A conversational AI system that analyzes XRPL AMM portfolio risk, generates quantitative trading strategies with visual risk profiles, and executes them on-chain via Bedrock smart contracts.
## Core Innovation
**Conversational Quant → One-Click Execution**
Traditional DeFi forces users to:
1. Manually calculate risk metrics
2. Research hedging strategies
3. Navigate complex DEX interfaces
4. Execute multiple transactions
This system compresses that into:
1. "Analyze my portfolio risk"
2. Review AI-generated strategies with risk graphs
3. Click "Execute"
## Architecture Overview
User Chat
  ↓
Local LLM (Intent Router)
  ↓ gRPC
Backend (XRPL Data + Quant Analysis)
  ↓
Quant LLM (Strategy Generation)
  ↓
Frontend (Risk Graphs + Action Buttons)
  ↓
Bedrock call.js
  ↓
Rust Smart Contract
  ↓
XRPL Native AMM
## Project Structure
- architecture/ — System design, data flow, API specs
- quant/ — Risk models, strategy algorithms, backtesting
- bedrock/ — Smart contract design, Rust implementation, XRPL integration
- llm-orchestration/ — Prompt engineering, LLM routing, context management
- references/ — Papers, docs, benchmarks
## Current Phase
**Research & Design (Week 1-2)**
- [ ] Define quant metrics (IL, delta, gamma, theta)
- [ ] Design strategy taxonomy (hedge, rebalance, exit, do-nothing)
- [ ] Prototype risk visualization (PnL curves, heatmaps)
- [ ] Map XRPL AMM API surface
- [ ] Bedrock smart contract proof-of-concept
## Key Questions
1. **Quant:** Which risk metrics matter most for retail XRPL AMM LPs?
2. **UX:** How do we visualize multi-dimensional risk without overwhelming users?
3. **Security:** How do we prevent the LLM from hallucinating dangerous trades?
4. **Performance:** Can we keep end-to-end latency under 3 seconds?
5. **Bedrock:** What's the optimal contract interface for strategy execution?
## Success Criteria
- **Accuracy:** Risk projections within ±5% of realized outcomes
- **Safety:** Zero unauthorized trades, strict slippage controls
- **Speed:** <3s from query to strategy presentation
- **Clarity:** Non-technical users understand risk trade-offs
## Next Steps
1. Build quant risk model for XRPL AMM
2. Prototype Bedrock smart contract
3. Design LLM prompt chain for strategy generation
4. Create mock risk visualization UI