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| _ \ __ _| |__ _ _| | | __ )| |__ __ _ _ __| |_(_)
| |_) / _` | '_ \| | | | | | _ \| '_ \ / _` | '__| __| |
| _ < (_| | | | | |_| | | | |_) | | | | (_| | | | |_| |
|_| \_\__,_|_| |_|\__,_|_| |____/|_| |_|\__,_|_| \__|_|
Full Stack Developer · Backend Architect · Agentic AI Builder
Currently employed. Quietly looking for something better.
Hey — I'm Rahul Bharti, a backend-heavy full stack dev who actually enjoys reading system design docs for fun.
I don't just build features — I build systems. Multi-tenant SaaS, video pipelines, async job queues, autonomous AI agents — that's my zone.
Right now I'm deep in Agentic AI with LangChain & LangGraph — building agents that do things, not just chat. The kind of stuff that makes you feel like you're writing science fiction.
- Creator & Lead Architect @ libspace.in — A production-grade, multi-tenant Library ERP serving real libraries.
- Building autonomous AI agents using LangChain, LangGraph & Gemini API.
- B.Tech IT Graduate (2025) · Global Rank #1961 in TCS CodeVita S12 (Top 0.5% / 537k+ devs)
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Backend runtime : Node.js · Express.js · TypeScript
python : FastAPI · Django
patterns: REST · Microservices · WebSockets
queues : BullMQ · RedisFrontend framework: React.js · Next.js
styling : TailwindCSSDatabases relational: PostgreSQL (+ Prisma ORM)
nosql : MongoDB
cache : Redis |
DevOps & Cloud containers: Docker
ci/cd : GitHub Actions
os : Linux
cloud : AWS · Azure · Google CloudAI / ML classical : Pytorch · Deep Learning
agents : LangChain · LangGraph
llm apis : Gemini API
current : Agentic AI · Deep Agent Arch.Specialized video : FFmpeg · HLS · Adaptive Bitrate
rt : WebRTC · Socket.io
infra : SRS · Bunny.net CDN |
📚 LibSpace — Library ERP SaaS
Not a college project. A real product.
Multi-tenant library management platform with QR-based attendance, automated billing, seat booking, and student productivity tools. Running in production, serving real institutions.
Node.js PostgreSQL Prisma Docker Multi-tenancy
🎬 Streamlet — Video Streaming Platform
Because "just use YouTube" isn't an answer.
Microservices-based video streaming with async transcoding via BullMQ, FFmpeg for HLS output, and adaptive bitrate delivery. Designed to scale.
Microservices BullMQ FFmpeg HLS Docker
💬 MeshTalk — P2P Video Calling
WebRTC in the wild.
Real-time peer-to-peer video calling and messaging. No middleman. Built on WebRTC + Socket.io.
WebRTC Socket.io MERN Stack
commit a3f91c2 feat: diving deeper into LangGraph multi-agent systems
commit 7b204e1 feat: building autonomous marketing agent w/ Gemini API
commit 2d9a0e0 docs: studying deep agent architectures & tool-calling patterns
commit 1c88f0d chore: exploring MCP (Model Context Protocol) integrations
I respond to interesting problems faster than O(1).
If you're building something ambitious in SaaS, AI agents, real-time systems, or video infra — let's talk.
"First, solve the problem. Then, write the code." — John Johnson