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Development case studyFintech Development

Developing an Investment Learning Platform With Courses, Labs, and a Trading Simulator

Seekho Invest connects educational content with practical market simulation through a multi-application architecture covering courses, labs, subscriptions, notifications, portfolios, orders, trades, and realtime ticks.

Featured projectSeekho Invest
Repository-backed development studyWAKA × Seekho Invest
Approved outcomeLearning + simulation platform
Next.jsNestJSWebSocketsRedis
Design focusLearning · Realtime · Fintech
Frontend
Next.js
Backend
NestJS
Realtime
Socket.IO and Redis
Data
PostgreSQL and Prisma
01 · Overview

Joining education and simulation without mixing their responsibilities

Seekho Invest combines several demanding product areas: course delivery, lesson progress, quizzes and labs, subscription access, notifications, and a simulated market with accounts, orders, trades, holdings, dividends, cash ledgers, and leaderboards.

The monorepo separates the customer frontend and API while keeping shared development scripts and continuous integration around the platform. The backend uses scheduled and realtime services for market ticks, Redis for coordination, and Prisma models for both learning and financial-simulation state.

ProductSeekho Invest
PlatformLearning and simulation platform
Development outcomeLearning + simulation platform
02 · The challenge

Keeping educational progress and trading state consistent in one product

Course progress can tolerate different timing and consistency rules than orders, positions, cash movements, and realtime prices. The platform needs to join these experiences for the learner while preserving clear service boundaries and testable state transitions.

01

Deliver courses, lessons, quizzes, labs, and progress tracking.

02

Support simulated accounts, orders, trades, holdings, dividends, and leaderboards.

03

Control features through memberships and subscription tiers.

04

Keep realtime market updates testable without depending on live exchange hours.

03 · Engineering decisions

Engineering choices that shaped the system

The architecture separates learning, commercial access, and simulation domains while connecting them through a shared identity and product experience.

01

Model learning and simulation as separate domains

Course, lesson, quiz, lab, and progress models remain distinct from orders, trades, holdings, cash, dividends, and portfolio snapshots.

Different state requires different boundaries
02

Use realtime services where timing matters

Socket.IO gateways, tick services, candle aggregation, and Redis support current market state without turning every product request into polling.

Realtime should be purposeful
03

Enforce access through feature and tier guards

Membership, subscription, and feature-access services control premium capabilities at the API layer.

Commercial rules belong in backend guards
04

Make market behavior reproducible in CI

The documented CI workflow runs against PostgreSQL and Redis while mocking simulator ticks so tests do not depend on live PSX data or market hours.

Determinism protects delivery
Approved outcomeLearning + simulation platform
01Learn
02Practice
03Simulate
04Review
Representative system visual. The development narrative is grounded in the monorepo, backend models, application modules, CI documentation, and test artifacts.
04 · System workflow

A learner journey from knowledge to controlled practice

The platform turns educational progress into guided practice without presenting simulated outcomes as real trading.

1

Learn

Work through structured courses, lessons, quizzes, and text or video material.

2

Practice

Use guided labs to apply concepts in controlled tasks.

3

Simulate

Place virtual orders and observe positions, cash, holdings, and market movement.

4

Review

Track progress, results, portfolio history, and achievements.

What the case demonstrates

A multi-domain fintech learning platform

  • Next.js learning and simulator frontend
  • NestJS modular API
  • Course, lab, and progress engine
  • Realtime simulated market services
  • Subscription and feature access controls
  • Automated unit and integration test infrastructure
05 · Outcome and evidence

An integrated codebase for structured learning and simulated market practice

The repository demonstrates a substantial platform where learning progress, gated product access, and realtime simulation can evolve as separate domains while remaining part of one user account.

22Lab routes

Numbered practical lab experiences present in the frontend

RealtimeSimulation

Socket.IO tick and market-state services

CI-backedDelivery

PostgreSQL and Redis test services with mocked ticks

Course, lesson, quiz, lab, and achievement workflows

Order, trade, holding, cash, dividend, and leaderboard models

CI designed to test simulator behavior without live-market dependency

06 · Key takeaways

What development teams can reuse from this work

  1. Educational state and financial-simulation state need different consistency and testing strategies.
  2. Realtime infrastructure should be limited to workflows that truly require current shared state.
  3. Feature access is safer when enforced in backend guards rather than UI visibility alone.
  4. Market simulation becomes testable when time and ticks can be controlled in CI.
Questions

About the project and its evidence

Does Seekho Invest place real stock-market orders?

The inspected code documents a learning platform and trading simulator. This case study does not claim brokerage execution or connection to a live exchange.

What realtime technology is present?

The backend includes Socket.IO gateways and Redis-backed simulator services for ticks, candles, orders, portfolios, and public ticker behavior.

How is the simulator tested outside market hours?

The repository documentation states that CI mocks simulator ticks and runs with PostgreSQL and Redis service containers, avoiding dependence on live PSX data or market hours.

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