LMS (LearnHouse-based) — Frontend, Backend & Deployment
Budget: $3000.0
FIXED /
⭐ 4.99 (16)
United Arab Emirates
next.js, python, javascript, react-js, artificial-intelligence, aws-application
Project Overview
We are building an Arabic-first (RTL) online learning platform. The core is built on top of LearnHouse https://github.com/learnhouse/learnhouse , a modern open-source LMS. We now need a capable development partner to extend it into a production-grade product and own its deployment.
We are specifically looking for an established company/agency, not an individual, because the scope spans frontend, backend, and DevOps/deployment and will run for several months.
Current Stack (you must be fluent in all of this)
Frontend: Next.js (App Router, output: standalone), React, TypeScript, Tailwind CSS, shadcn/ui
Backend: Python, FastAPI, SQLModel, Alembic migrations
Database: PostgreSQL with pgvector (vector embeddings for AI search)
Realtime/Collab: Yjs / Hocuspocus (websocket-based collaborative editing)
AI: OpenAI integration (chat + embeddings)
Infra: Docker / docker-compose, nginx, pm2, Redis
i18n: Full Arabic RTL + English LTR support
What We Need
Feature development on top of the existing codebase — new modules, custom flows, and UI work (we will share a detailed roadmap with the selected partner).
Backend/API work — FastAPI endpoints, data modeling, migrations, and AI features grounded on course content.
Arabic-first UX — flawless RTL rendering, Arabic typography, and bilingual content.
Deployment & DevOps — production deployment (cloud hosting, CI/CD, monitoring, backups), scaling, and ongoing maintenance.
Required Qualifications
Proven agency experience with Next.js + FastAPI + PostgreSQL production apps (please share portfolio links).
Experience forking and extending an existing open-source codebase (not just greenfield builds).
Strong Docker / deployment track record (AWS, GCP, Railway, Render, or similar).
Arabic-language / RTL product experience is a strong plus.
A team that can cover frontend, backend, and infra concurrently.
Nice to Have
Prior LMS or EdTech experience.
AI/RAG (retrieval-augmented generation), pgvector, or LLM integration experience.
To Apply (please include)
A short note on how you would approach extending an existing Next.js + FastAPI codebase (not generic copy-paste proposals).
2–3 relevant case studies with live links and your specific role.
Your team composition (who does FE / BE / DevOps) and team size.
Your availability and typical engagement model (dedicated team, retainer, fixed-bid).
Confirmation you've read this post — start your reply with the word "Athar" so we know.
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