TradeFrame
AI-Powered Trading Infrastructure for Retail Investors
MVPActiveFinTechFounded 2026
- ActiveBacktesting Engine
- Multi-ExchangeMarket Data Sources
- Event-DrivenArchitecture
- Retail TradersTarget Market
The Challenge
Retail traders operate with the same market data as institutions but without the infrastructure to process it. Most retail tools offer basic charting and manual execution — a knife in a gunfight. The result: emotional trading, poor risk management, and systematic wealth destruction. Institutional tools exist but cost $50K+ annually and require quantitative expertise to operate.
The Solution
TradeFrame democratizes institutional-grade trading infrastructure — delivering algorithmic execution, portfolio optimization, and risk management through an accessible platform built for disciplined retail traders. Every tool is designed for production use: backtested against real market data, stress-tested against tail risk events, and built with the same architectural rigor we apply to all HavenWizards ventures.
Want to build something like TradeFrame?
We deploy the same production-grade systems powering this venture to partner projects. No prototypes — real infrastructure, real operators.
How We Built It
The Vision
TradeFrame is being built as an institutional-grade trading infrastructure platform designed for retail investors who refuse to trade blind. The platform brings algorithmic precision, real-time market analysis, and portfolio optimization tools that were previously locked behind six-figure minimums at hedge funds — and puts them in the hands of disciplined retail traders.
What We Build
- Algorithmic Trading Engine: Custom strategy builder with backtesting across historical data, real-time signal generation, and automated execution with risk controls
- Portfolio Intelligence: Multi-asset portfolio analytics with correlation mapping, risk-adjusted return tracking, and rebalancing recommendations
- Market Analysis Pipeline: Real-time data aggregation from multiple exchanges, sentiment analysis, and technical indicator computation at institutional speed
- Risk Management Framework: Position sizing, drawdown protection, and exposure monitoring — the guardrails that separate trading from gambling
The Architecture
Built on a high-throughput event-driven architecture — Python for quantitative computation, Node.js for real-time WebSocket feeds, PostgreSQL for historical data warehousing, and Redis for sub-millisecond caching. The platform processes market data streams with institutional-grade latency while maintaining the reliability required for automated execution.
Future Expansion
- Multi-exchange connectivity (crypto, forex, equities, commodities)
- Social trading layer — follow and replicate verified strategies
- AI-powered strategy optimization using reinforcement learning
- Mobile companion app for monitoring and alerts
- API marketplace for third-party strategy providers
Tech Stack
PythonFastAPIReactPostgreSQLRedisTensorFlow
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