Hi, I'm Hanzla Sadaqat
MERN & AI Automation Engineer
I build full-stack apps and wire LLMs into real workflows.
About Me
A bit about who I am and what I do.
I'm a full-stack developer focused on the MERN ecosystem (MongoDB, Express, React, Node) and AI automation.
I help teams ship production web apps and replace repetitive work with LLM-powered automations — Gmail triage, document parsing, lead enrichment, internal copilots.
- •3+ years building production MERN applications
- •Designed and shipped 10+ AI automation pipelines
- •Comfortable across the stack: from Mongo schemas to Tailwind UI
- •Tooling: OpenAI, LangChain, n8n, Make, Zapier, Pinecone
Projects
A selection of things I've built recently.
MERN e-commerce dashboard with Stripe payments, inventory tracking, and analytics. JWT auth, role-based access.
Mobile-first habit tracker with streak analytics, dark mode, and PWA install. Offline-first via service workers.
AI Automations
Real workflows I've built and the impact they had.
Lead Enrichment Pipeline
Sales team spent 6+ hours/week manually researching leads on LinkedIn.
Built an n8n + OpenAI pipeline that pulls leads from a CRM, enriches with Apollo, summarizes the company, and writes a first-touch email draft.
~5 hours/week saved per rep; reply rate up 23%.
Support Ticket Auto-Triage
Inbox of 200+ daily tickets, slow first-response times.
LangChain classifier + RAG over the help-center docs. Tickets are tagged, routed, and answered with a draft reply that the agent edits.
First-response time cut from 4h to 12 min.
Invoice OCR + Sheets Sync
Finance was manually keying invoices into Google Sheets.
Make scenario watches a Drive folder, runs GPT-4o vision OCR, normalizes fields, and appends rows with validation.
~12 hours/month reclaimed; 99% extraction accuracy.
Blog
Notes on what I'm building and learning.
Building a RAG system that actually answers questions
Most RAG demos look great. Most production RAG systems hallucinate. Here's what changed when I shipped mine.
MongoDB schema patterns I wish I knew at 22
Embedding vs referencing, when to denormalize, and the mistake I keep seeing in MERN starter repos.
n8n vs Make vs Zapier: choosing an automation tool in 2025
A decision tree based on 30+ pipelines I've shipped — what each tool is actually good at.
Resume
My experience and education.
AI Automation Engineer
2024 — present- •Designed LLM workflows in n8n and LangChain for 5+ SMB clients.
- •Cut manual ops work by 40+ hours/week across deployments.
- •Stack: OpenAI, Pinecone, LangChain, n8n, Make.
Full-Stack Developer (MERN)
2022 — present- •Built 10+ production MERN apps for clients in e-commerce, edtech, SaaS.
- •Owned the full lifecycle: Mongo modeling, Express APIs, React UI, deploys.
Junior Developer
2021 — 2022- •Shipped React frontends and Node services for client websites.
- •Wrote integration tests and set up CI on GitHub Actions.
B.Sc. Computer Science
Get In Touch
Have a project in mind? Let's talk.
Whether it's a MERN build, an AI automation idea, or just to say hi — drop a message and I'll reply within 24 hours.