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Case Study

Claxton Quant Pro Trader

An institutional-grade options trading platform — built from zero to production in under a week, demonstrating the power of AI-augmented development.

47,000+
Lines of Code
327
Passing Tests
<1 Week
Total Build Time
100%
Documentation Coverage

The Challenge

Build an institutional-grade options trading platform from scratch — including a quantitative trading engine, real-time dashboard, comprehensive documentation, and multi-broker integration. The kind of project that typically takes a team of engineers months to deliver.

The Solution

Leveraging AI-augmented development workflows, I built a full-stack trading system combining a Python quantitative engine, React dashboard, and comprehensive documentation — all following enterprise development standards with proper testing, CI/CD, and production deployment.

PythonFastAPIReactTypeScriptNext.jsPostgreSQLDocusaurusDockerMulti-Broker APIs

Deliverables

Trading Engine

Python-based institutional options trading engine with multi-strategy support, risk management, and real-time market data processing.

React Dashboard

Interactive real-time dashboard for monitoring positions, P&L, risk metrics, and executing trades across multiple brokers.

Documentation Site

Comprehensive Docusaurus-powered documentation covering architecture, API reference, deployment guides, and user manuals.

Test Suite

327 automated tests covering unit, integration, and end-to-end scenarios with continuous integration pipeline.

Multi-Broker Architecture

Abstracted broker interface supporting Schwab, Tradier, and IBKR with unified order management and position tracking.

Deployment Infrastructure

Production-ready deployment with Vercel-hosted frontend, containerized backend services, and monitoring.

Need this kind of output for your project?

Whether it's documentation, a complete technical writing overhaul, or a full-stack prototype — I deliver enterprise quality at startup speed.

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