Competitive mini-game platform with cash prizes
72D web mini-games in production
Client
Gaming platform (undisclosed client, NDA)
Year
2026
Stack
2D web engine + TypeScriptWeb portal (PWA)Serverless Node back-endNoSQL + relational databasesInfrastructure as code + WAFPIXGenerative AI
Links
Game development at JBKR ↗

The challenge

Build from scratch, in months, a platform where real money comes in and goes out through PIX and a player's score is worth a prize: cheating had to become expensive and detectable, the books had to balance to the cent, the games had to be proven games of skill rather than chance, and everything had to be operated by a small team.

The objective

Launch seven mini-games with three-player rooms, ranking, missions, a store and PIX payments, with a complete audit trail and a gradual launch without interrupting operations.

The solution

Game client on a 2D web engine with TypeScript, WebP atlases and per-game asset packs; web portal (PWA, several languages) and admin panel; serverless Node back-end with a real-time NoSQL database and a relational database (179 endpoints), a dual-write ledger with audit tables, idempotent processing and a circuit breaker on the PIX gateway; anti-cheat with HMAC-signed scores, server-generated seeds and layouts, a honeypot, replay auditing and an obfuscated build; bots filling incomplete rooms and statistical skill-versus-luck simulation; managed authentication with MFA, anti-bot verification, app attestation and identity verification; infrastructure as code (network, edge WAF, permissions, secrets), managed queues and a data warehouse; CI against emulators; a generative-AI coach and automatic rhythm-map generation from audio.

The impact

  • Seven mini-games in production on a single platform, with three-player rooms, tiered MMR ranking, missions, streaks, a store and subscriptions
  • 179 back-end endpoints, 253 test files and 67 recorded architecture decisions in about six months
  • PIX cash flow with an auditable ledger and idempotent processing, identity verification before withdrawals and MFA for administrators
  • Gradual launch with separate production and staging environments and the whole infrastructure as code
Jean C Becker

Jean C Becker

Senior Solutions Architect | AI & Machine Learning Specialist

Designed and built this work. About JBKR →