Before products, data
I learned to build by learning to read.
Before I wrote software for other people, I spent years with spreadsheets, SQL and dashboards — learning what a pile of numbers is quietly trying to say.
Full-stack developer — Vadodara, India
I design and build web platforms end to end — the screens people use and everything that keeps them fast, secure and online.
Open to work · full-time, freelance, consulting
Move through the name · click for a ripple
The journey
From a first program to products in production — one line, five turning points.
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2019
Started a B.Sc. in IT
P P Savani University · Surat
First programs, first databases — and a habit of taking things apart.
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2022
Data analyst
Disha Info Tech · Pune
Turned business data into Power BI and Tableau dashboards.
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2023
M.Sc. in IT
MSU Baroda · Vadodara
Data science and machine learning — including New York taxi data.
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2025
Full-stack developer
Webbrains Technologies · Vadodara
Five client products across healthcare, enterprise, e‑commerce and hospitality.
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Now
Open to the next thing
Full-time · Freelance · Consulting
Looking for a team where the hard part is making it work.
Data, made visible
One day of New York in 97,003 real taxi rides — and then 800 pieces of my own work.
A day in New York
Every dot is a real taxi pickup.
This is New York on Thursday, 15 January 2015 — 97,003 yellow-cab trips from the city's open data. The avenues of Manhattan draw themselves.
- Typical ride
- 10.6 min
- Average trip
- 2.8 miles
- From airports
- 3,733
Scroll through the day
Watch the city breathe.
Quiet at 4 am — just 335 pickups. Busiest at 10 pm with 7,248. At 11 am traffic crawls at 9 mph; at 4 am cabs fly at 20.
The research
Can you predict how long a ride will take?
In my M.Sc. I used New York taxi trips like these to find out: cleaned the data, found patterns in when and where rides start, and tested six prediction models side by side. The tree-based models won.
PythonPandasscikit-learn6 models5-fold checks
Read the case study →Today, my own data
Every square is one endpoint I've built.
An endpoint is a doorway an app's features walk through — log in, book a visit, issue stock. Here are all 800 of them, by product.
- 406Cure & Care
- 169TATA Advanced Systems
- 146DemandTrans
- 79Study-Flow
Data: NYC Taxi & Limousine Commission trip records, via kepler.gl-data
What I've built
Every tower is a doorway into a feature. Every district is a product people use every day.
Cure & Care
One platform for patients, doctors and pharmacies.
Patients book visits and order medicines. Doctors run their day and send prescriptions. Admins manage everything. Four apps share one backend — so every screen updates the moment something changes.
- 4apps
- 1shared backend
- Livesince 2025
TATA Advanced Systems
Every part, every shelf, every movement — accounted for.
An inventory system for an enterprise manufacturer. Staff sign in with their company accounts, stock is tracked rack by rack, and every movement is recorded with who did it and when.
- 3staff roles
- 100%moves recorded
- Autoshift reports
DemandTrans
Content and products, managed in one place.
A content system for a corporate website and product catalogue. Every edit is checked and recorded, and the whole system is packaged to run the same way on any server.
- 29data models
- Everyedit recorded
- Portableruns on any server
Study-Flow
Study together, live.
Virtual study rooms with live focus timers, streaks, badges and leaderboards. Everyone in a room sees the same thing at the same moment — and it stays that way as more people join.
- Livestudy rooms
- 12automated jobs
- Paidsubscriptions
Hospitality booking
Fast pages, even on the busiest days.
The engine behind a hotel booking site: popular pages served instantly from memory, and protection that keeps bots and bad requests out — so real guests always get through.
- Instantpopular pages
- Botprotection
- Safeinputs
Six floors
Look inside any tower and it's built the same way. I work on every floor — so nothing gets lost between them.
- 06
What people see
Clean, fast screens for patients, doctors, admins or warehouse staff.
- 05
How it works
The rules behind every button — who sees what, and what happens next.
- 04
What happens live
Bookings and messages that update on every screen at once.
- 03
On autopilot
Reports, reminders and emails that send themselves on time.
- 02
What it remembers
Data organised to stay quick as the product grows.
- 01
Where it lives
On the cloud — secured, monitored and kept online.
Real time
The best software changes the moment the world does. Everything I build is made to react instantly — on every screen at once.
Live Try it
Everyone sees it the moment it happens.
Book a slot on the patient's phone. The doctor's schedule and the clinic dashboard update instantly — no refresh, no double bookings.
9:41
Book a visit
Dr. Anjali Mehta
Cardiology · Tue, 14 Oct
Tap a time to book it
Today · Dr. Mehta
- 09:00Riya Shah
- 09:30Open
- 10:00Open
- 10:30Arjun Patel
- 11:00Open
- 11:30Open
- 12:00Meera Iyer
- 12:30Open
New booking
Bookings today
23
Live feed
- 08:52 Clinic booking · Dr. Rao
- 08:40 Video visit · Dr. Mehta
- 08:31 Lab test ordered
Process How I work
Four steps, no surprises.
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01
Listen
We talk about the problem, the people who'll use the product and what success looks like. No jargon — just a clear picture of what we're building and why.
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02
Blueprint
Before writing code, I map the screens and the data underneath them — so the foundation fits the product, and changes later are cheap instead of painful.
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03
Build
Weekly progress you can click through yourself. Security and speed are built in from the first day — not bolted on at the end.
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04
Launch & look after it
Deployed, monitored and kept healthy. If something goes wrong at 2am, it's already in the logs — and usually fixed before anyone notices.