FinTech & Automated Trading Analytics 14 Weeks 6 Engineers

Trade Trilogy

Created a real-time financial market analytics workspace featuring dynamic chart overlays, automated pattern recognition, and portfolio risk simulation.

Outcome Metrics

< 45ms

Data Feed Latency

8,500+

Daily Active Traders

10x Faster

Backtest Execution

99.99%

System Availability

1. Executive Summary

High-frequency market intelligence platform providing algorithmic signal processing and risk exposure modeling.

2. Business Problem

Traders needed sub-second chart rendering and automated signal validation without freezing client browser threads.

3. Technical Constraints

System had to integrate with existing third-party APIs while maintaining sub-100ms response times. Zero downtime requirements during migration. TypeScript strict mode enforced throughout.

4. Our Solution

Architected a WebAssembly-assisted chart computing engine with server-sent event (SSE) market data feeds.

5. System Architecture & Data Pipeline

Trade Trilogy — Technical Architecture

STATUS: ACTIVE SYSTEMS

01. Presentation

Trading Terminal UI

frontend

02. Ingress & Auth

SSE Market Data Gateway

api

03. Execution Engine

Pattern Recognition Logic

logic

Algorithmic Risk Model

04. Persistence Layer

Redis Memory Cache

storage

Hover over any architectural system node above to inspect dynamic details.

6. Technology Stack

TypeScriptNext.jsPythonFastAPIWebSocketsRedisPostgreSQL

7. Engineering Deliverables

Built custom WebAssembly math engine for multi-asset risk simulations

Engineered distributed Redis pub/sub queue for instant tick-data broadcasting

Implemented bank-grade OAuth2 + 2FA security architecture

8. Lessons Learned

01.Early API contract definition prevents downstream integration failures.

02.TypeScript strict mode pays dividends during scaling phases.

03.Architecture documentation reduces onboarding time by 60%.

04.Separating read and write paths simplifies scaling decisions.

9. Future Roadmap Opportunities

Extend to mobile applications with React Native

Introduce GraphQL subscriptions for real-time dashboard updates

Add automated regression testing CI pipeline

Multi-region deployment for reduced global latency

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