Hi, I'm

Muaaz
Shaikh <3

I design & build AI systems and
ship them to production.

AI engineer specializing in agentic workflows, LLM pipelines, and production ML systems. I turn research into shipped products.

Muaaz Shaikh mascot
✦ BUILDER ✦
AGENTIC AILANGGRAPHFULL-STACKPRODUCTION-GRADEFASTAPIHACKATHON WINNEROPEN SOURCEREACTNEO4JLANGCHAINDOCKERTYPESCRIPTAGENTIC AILANGGRAPHFULL-STACKPRODUCTION-GRADEFASTAPIHACKATHON WINNEROPEN SOURCEREACTNEO4JLANGCHAINDOCKERTYPESCRIPT
Expertise

What I Build

Agentic AI Systems

Multi-agent workflows using LangGraph, LangChain with tool-calling, memory, planning, and state transitions.

AI Backend Engineering

Fast AI backends: async pipelines, WebSocket streams, GraphQL and REST APIs, real-time AI integrations.

Machine Learning Systems

End-to-end ML pipelines from data preparation to deployment, model monitoring, and retraining workflows.

Applied Research

Applied research in legal AI and healthcare, including fine-tuning BERT, LLaMA, and building custom evaluation workflows.

Projects I've Worked On 🚀

Real systems, shipped to production.

SuperGraphene screenshot

SuperGraphene

Full-stack cybersecurity investigation platform using React, FastAPI, Neo4j, and graph analytics. Unifies SOC, AML, and identity signals into a single graph. AI agents run autonomous investigations and auto-generate FIU-IND Suspicious Transaction Reports, cutting analyst workload from hours to minutes.

ReactFastAPINeo4jLangGraphGANsDocker
Lorri AI screenshot

Lorri AI

ML + Operations Research platform improving fleet utilization to 94.6%. Combines RandomForest demand prediction (F1=0.93) with OR-Tools route optimization, explainable agentic decision workflows, and scenario simulation engine for dynamic routing strategies.

FastAPILangGraphscikit-learnOR-ToolsGemini 2.0ReactDocker
Serene.AI screenshot

Serene.AI

Multi-agent conversational AI system using LangGraph orchestration. Hybrid RAG pipeline (FAISS + BM25) with source-grounded responses, multi-layer memory including episodic, long-term, and semantic recall. 1.2–1.5s latency with safety guardrails and escalation logic for high-risk emotional states.

LangGraphFAISSMongoDBFastAPIReact
SuperMuseum — AI Cultural Guide screenshot

SuperMuseum — AI Cultural Guide

AI-powered interactive digital museum with a gamified isometric pixel-art environment and multilingual agentic RAG guide. Users explore Indian heritage through personalized tours in 10+ languages. Winner of the Experience India Track at IndiaStack Build for Billions Hackathon at NITK Surathkal.

LangChainLangGraphFastAPISarvam AIJioSaavn API
Taqneeq Fest App screenshot

Taqneeq Fest App

Cross-platform fest app (Android, iOS, Web) with 200+ users. Built Polaroid-style memory frames, live map event navigation, gamified QR stall interactions, and vision-based photo clustering using FaceNet so attendees could find photos of themselves automatically. Led backend systems and deployments.

FastAPIReact NativePostgreSQLDockerOpenCVFaceNet
🔍

SuperHoax.AI

Agentic misinformation detection system that identifies and verifies viral claims during global crises. Specialized AI agents monitor social media and news in real time, cross-checking claims against credible sources. Builds dynamic reputation scores for information sources, enabling faster trust decisions at scale.

FastAPILangGraphGeminiTavily SearchReactDocker
Private repository

Battle Tested 🏆

3 wins, 4 podium finishes. Problems solved under pressure.

WinnerApr 2026

Open Paws Data Visualization Hackathon

Data Paws
WinnerApr 2026

ACM Semicode Coding Contest

WinnerNov 2025

Build for Billions: IndiaStack Hackathon

SuperMuseum
1st Runner-UpApr 2026

KODE-IET Hackathon Finale

SuperGraphene
Runner-UpNov 2025

IEEE HackXplore Hackathon

Ra.AI
Runner-UpAug 2025

IETE-SF ACE

Ra.AI
2nd Runner-UpMar 2026

Taqneeq CyberCypher 5.0

Lorri AI
Loading contributions...

My Roadmap

From foundations to scale. A journey in building AI.

Phase #01 // completed

Foundation Building

Built strong foundations in machine learning, deep learning, and backend engineering through coursework, certifications, and hands-on projects. Focused on understanding core ML concepts while actively building.

Phase #02 // current

Systems & Research

Currently building production AI systems: agentic workflows, LLM pipelines, and applied research in legal AI and healthcare monitoring. Focused on shipping real products.

Phase #03 // next

Scale & Impact

Aim to scale AI systems, publish research, and contribute to open-source ecosystems. Building toward global AI engineering or applied research opportunities.

Blogs

Thoughts on building AI systems, research, and engineering.

Engineering2026-02-18·6 min

What Building Real AI Systems Taught Me (That Courses Don't)

From models to production: lessons from shipping AI used by real users.

Read on Medium
AI Systems

From RAG to Agentic AI: What Actually Changed?

Lessons from building real multi-agent AI systems and why the paradigm shift matters.

Coming Soon
Research

Why LoRA & QLoRA Work So Well for Legal Summarization

Practical insights from fine-tuning LLMs for long-form legal documents at scale.

Coming Soon

Get In Touch

Let's build something incredible together.

Or reach out directly: