Six steps to
autonomous trading.
Data Infrastructure
Event-driven pipeline with RabbitMQ, worker pools, and structured storage. Multi-service architecture with React frontend, Python API, Ollama runtime, and domain-based message routing.
Services
Generation
Queues
Workers
Neural Search Engine
RAG implementation combining Pinecone vector DB with Ollama LLMs. Hybrid storage — embeddings in Pinecone, large payloads offloaded to S3 with signed URL generation and automatic threshold management.
Vector DB
Pinecone + S3 links
S3 Storage
Auto-offloading
Alpha Signal Generation
LLM-powered financial signal extraction with confidence scoring. RAG-enhanced reasoning uses retrieved market data and news sources. Full source attribution for signal verification.
Backtesting Framework
Historical simulation with walk-forward validation, performance metrics, strategy comparison, and risk-adjusted return calculation.
Risk Management
Dynamic position sizing, drawdown protection, portfolio heat mapping, real-time risk monitoring, and stress testing.
Live Trading Bot
Paper trading integration, broker API connectivity, real-time execution engine, monitoring dashboard, and alert system.