Freelancers using Node.js in Islamabad Capital TerritoryFreelancers using Node.js in Islamabad Capital Territory
Full-Stack Dev | Typescript, Next.js, Supabase, AI Agents
$25k+
Earned
4x
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5.0
Rating
97
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Full-Stack Dev | Typescript, Next.js, Supabase, AI Agents
Full Stack Developer | Blockchain | Mobile Apps | Web Apps
5.0
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18
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Full Stack Developer | Blockchain | Mobile Apps | Web Apps
React Native & Node.js Developer | AI Apps | UI/UX
5.0
Rating
17
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React Native & Node.js Developer | AI Apps | UI/UX
🚀 AI & Fullstack Developer | MERN Expert 🚀
$10k+
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5x
Hired
5.0
Rating
28
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🚀 AI & Fullstack Developer | MERN Expert 🚀
Full Stack Developer| n8n | Framer| Kajabee| Webflow Expert
1x
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43
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Full Stack Developer| n8n | Framer| Kajabee| Webflow Expert
AI SaaS Dev | LLMs, Agents, Voice & Automation | Web, Mobile
New to Contra
AI SaaS Dev | LLMs, Agents, Voice & Automation | Web, Mobile
Cover image for GYMYG — Virtual Fitness Platform
California,
GYMYG — Virtual Fitness Platform California, USA · 12 Months · 7-Person Team The Problem The home fitness market exploded but the tech never caught up. Existing solutions were either pre-recorded content with no real interaction, or basic video calls with no fitness intelligence built in. GYMYG needed something that didn't exist yet — a platform where certified trainers and clients could train together in real time, with the intelligence to match them, program for them, and keep them accountable long after the first session. What We Built A complete virtual fitness ecosystem — two separate applications for trainers and clients, coordinated through a single backend, with an admin layer running everything underneath. Sessions run over WebRTC with adaptive bitrate streaming, so video quality adjusts automatically based on connection strength without dropping the call. TURN/STUN resilience means sessions stay live even on difficult networks. In 50,000+ sessions delivered, the failure rate never crossed 1%. The AI layer does the work that makes GYMYG more than just a video call. Programming is calibrated to each user's goals and adherence patterns — if someone keeps skipping leg day, the system knows. Biometric and session telemetry track safe progression and flag recovery needs before they become injuries. Trainer-client matching uses availability, specialty, and historical satisfaction signals — not just whoever's online. Community features — live group classes, asynchronous content, and moderated chat — were built in from day one because retention data is clear: people who train alone quit. People who train in community don't. Technical Architecture Real-time sessions: WebRTC with adaptive bitrate streaming + TURN/STUN resilience Backend: Node.js services layer handling real-time state, scheduling, and payments Database: MongoDB with rigorously designed schemas and TTL-based event retention Infrastructure: AWS with autoscaling, managed queues, and full-stack observability — metrics, logs, traces Security: Tokenized access, scoped permissions, encrypted media signaling throughout Stack: React Native · Node.js · WebRTC · MongoDB · AWS Results 50,000+ live sessions delivered 95% customer satisfaction across rolling quarters Sub-1% session failure rate Improved 90-day retention driven by social features and AI-personalised programming First live fitness app to offer real-time trainer-client interaction at this scale Successfully launched into the US fitness market in 12 months What This Proves Real-time platforms at scale aren't just a backend problem. They're an architecture problem. The decisions made in month one — how sessions are handled, how data is structured, how the AI layer sits inside the product — are what determine whether you hit 50,000 sessions or fall apart at 500. GYMYG was built to handle the former from day one.
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