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Soundcheck
Built an automated pre-recording verification tool that checks a complex Windows audio and OBS setup before a recording session begins. Instead of manually checking dozens of settings, the tool validates them automatically and only interrupts the user when something is wrong.
The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started
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How I Built a 60 FPS Real-Time Esports HUD Builder & WebGL Broadcast Engine for BLOB
Live esports broadcasts don’t forgive dropped frames.
When competitive titles like Valorant, Counter-Strike 2, and Rocket League stream tournament telemetry at 60 updates per second, standard React virtual DOM reconciliation simply chokes under the load in OBS Studio. I was brought on by BLOB Productions following a competitive head-to-head architectural evaluation to completely re-engineer their broadcast overlay infrastructure from the ground up.
What We Built:
- 60 FPS Headless HUD Engine: Built a renderer-independent JSON scene graph with Figma/Rive-grade interaction math (multi-selection, aspect-ratio locked transforms, boolean operations, and 360° pivot rotations).
- Complete Vector & Style Stack: Multi-fills with linear/radial gradients, multi-strokes, inner/drop shadows, per-corner radiuses, blend modes, and Gaussian blurs.
- Reactive Data & Motion Logic Engine (Core IP): Continuous value mapping (e.g., player health mapped to visual bar width), dynamic scope inheritance across duplicated player cards, repeaters, and event-driven trigger animations.
- Ultra-Low Latency OBS Runtime: A lightweight PixiJS (WebGL) runtime with signal-based direct node mutations and a jitter-smoothing dead reckoning buffer—maintaining $<16ms Time-to-Glass.
- Zero-Egress Client-Side Edge Merge: Merged high-frequency P2P/WebSocket telemetry directly on the client edge with static tournament metadata, eliminating expensive cloud compute bottlenecks.
- Cloud Persistence & Publishing Pipeline: CockroachDB/PostgreSQL draft-versus-live isolation, version rollback, and an automated P0 verification test suite.
Read the full case study with architectural diagrams and demo breakdown here: 60 FPS Real-Time Esports HUD Builder
Looks rrally cool!
Automated Trading Signal Analytics
A real-time analytics module for monitoring and evaluating automated cryptocurrency trading signals.
The system automatically stores and analyzes generated BUY, SELL, and HOLD signals, tracks confidence scores, records market prices, and provides performance statistics directly through a Telegram interface.
Key features:
Automated BUY / SELL / HOLD signal tracking
Real-time signal statistics
Confidence score monitoring
Historical signal logging
Trade performance and PnL analytics
Win rate tracking
PostgreSQL data storage
Telegram reporting interface
Automated background monitoring
This analytics module is part of a larger Python-based automated market analysis and demo trading system.
Built an automated LinkedIn content publisher — a system that generates, schedules, and posts LinkedIn content on autopilot, backed by a database-driven content pipeline.
