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Multi-agent AI trading platform with RAG pipelines for autonomous trading decisions. TradingView-style dashboard with intelligent infrastructure.
Multi-Agent
AI Architecture
RAG-Powered
Decision Engine
The Challenge
Building autonomous trading systems that can make intelligent decisions with full explainability.
- Trading decisions require synthesising vast amounts of market data in real-time
- Traditional systems lack the ability to reason about context and historical patterns
- Execution timing and risk assessment need coordinated decision-making
- Full audit trails and explainability are essential for trust and compliance
Our Solution
Built a multi-agent AI system with RAG pipelines and structured decision frameworks.
- Multi-agent architecture with specialised agents for analysis, risk, and execution
- RAG-enhanced context using vector embeddings across historical market data
- Decision point framework with multiple gates requiring consensus
- Chain-of-thought reasoning with full explainability and audit trails
- TradingView-style dashboard for monitoring and control
The Outcome
Production-grade autonomous trading infrastructure with intelligent decision-making.
- Coordinated AI agents work in parallel for comprehensive market analysis
- Semantic search across thousands of annotated market scenarios
- Structured outputs with confidence intervals and risk metrics
- Full observability with comprehensive monitoring and performance tracking
Technology Stack
PythonFastAPIPostgreSQLReactTypeScriptDocker