Overview

ForgeX Trading lets traders practice strategies against historical market data, replaying charts and placing simulated orders before risking real money. I helped build the initial platform with Advay, turning the product vision into a working trading terminal and the data infrastructure behind it.

Role and constraints

As Founding Full-Stack Engineer, I did most of the initial coding and made the technical architecture decisions. Advay led the product vision, and I helped him contribute to the code through his AI agents. My involvement ran from May through August 2026 and included migration support and developer onboarding to hand off the platform.

Process

I built the initial application, core buy/sell functionality, and chart-history and replay behavior using Python, FastAPI, and React. Replay improvements included stable chart viewports, weekend context, chart synchronization, and journal refresh behavior.

For historical market data, I implemented QuestDB time-series storage, batched candle ingestion, and incremental synchronization. Gap-filling and recency updates extended the available history without repeatedly loading existing data. I also added database backup, restore, and candle-merging tooling, integrated multiple AI providers, and documented deployment.

Result

The platform I helped establish now serves more than 150 users, as reported in my October 2026 resume. That adoption reflects the product’s continued development after my initial work and handoff.

Market replay with an active simulated trade and stop-loss and take-profit levels. Dashboard with account performance, trade distribution, and recent replay sessions. Trade review with entry and exit chart captures and reflection fields. Performance analytics with an equity curve and trading statistics. AI coaching report with an edge rating and strategy analysis. Simulated order entry with direction, order type, quantity, and risk controls.