Vaibhav Sharma
I build custom software that solves real business problems
New to Contra
Vaibhav is ready for their next project!
I just finished working on this project! 🚀
NursingLedger combines four major CMS data sources into detailed profiles for every covered facility. Visitors can search by facility name, city, state, or ZIP code; compare homes side by side; explore ownership relationships; review federal penalties; examine payroll-reported staffing; and browse records across every state.
Some highlights from the build:
→ 14,693 certified nursing facilities published as searchable profiles
→ 16,166 federal penalty records organized and connected to the correct facilities
→ 247,632 reported ownership records transformed into understandable relationships
→ Payroll-reported staffing data covering 14,478 facilities
→ 14,880 discoverable pages submitted through a production-ready XML sitemap
→ Search, state directories, ownership groups, watchlists, and facility comparison tools
→ Fully responsive layouts across desktop, tablet, and mobile devices
→ Structured metadata, canonical URLs, schema markup, social previews, robots rules, and scalable programmatic SEO
→ A static edge architecture designed to keep thousands of data-rich pages fast, reliable, and inexpensive to serve
One of the most interesting parts was preserving the meaning of the source data. Missing values remain missing, calculated figures are clearly separated from imported CMS fields, and rankings are never presented as conclusions the underlying records cannot support.
This project brought together data engineering, product design, frontend development, technical SEO, accessibility, responsive testing, and production infrastructure. The best part is that all of that complexity stays behind the scenes. For the visitor, it feels like a clean website that answers an important question:
“What does the public record actually say about this nursing home?”
Live project: HERE (https://nursingledger.com/)
Really proud of how this one came together, especially the balance between serious public data and an experience that still feels approachable and easy to navigate.
Looking forward to building more ambitious, data-driven platforms for clients here on Contra! 🤝
Cheers, and thanks for reading!
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I just finished working on this project! 🚀
MotorCensus is a data-driven vehicle research platform built to help people understand what owners actually report before they buy.
At its core is the U.S. federal vehicle complaint record: the public NHTSA ODI dataset, where car owners across America file complaints about real problems with their vehicles. I built a pipeline that ingests over 2.1 million raw complaint rows, cleans and deduplicates them into 398K matched incidents, and turns them into statistically honest reliability signals for every covered model year.
This one was a fun challenge because it is not just a website. It brings together a large complaint dataset, model-year normalization, signal scoring, filtering, comparison flows, and hundreds of structured pages while keeping everything fast and easy to navigate.
A few technical highlights:
-> 2.1M+ raw NHTSA complaint rows processed into 398K+ deduplicated complaint incidents
-> 731 evidence-qualified model-years, each published with sample sizes and bootstrapped 95% confidence intervals
-> Cohort-relative signal scoring: a 2013 midsize sedan is only ever compared against 2011 to 2015 midsize sedans, never against the whole market
-> Complaint signal scoring and model-year comparisons
-> Dynamic browse and research flows across 800+ statically generated pages
-> SEO-ready architecture with generated sitemaps and production indexing
-> Performance-focused static architecture with a tiny JavaScript footprint, so every page loads fast
The tricky part was making a technically heavy data system feel simple and intuitive for someone who just wants to answer one question:
"Should I actually buy this car?"
Live link: HERE (https://motorcensus.com/)
Really happy with how this one came together.
Looking forward to working with clients here on Contra! 🤝
Cheers, and thanks for reading!
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I just submitted my entry to the Replit Buildathon! 🚀
I built ClientOS, a client-work dashboard designed to bring projects, approvals, updates, and payments into one clean workflow.
The client side is just as important: clients can open a private portal, review deliverables, approve work, and pay invoices without needing to create an account.
Live app: HERE (https://dashboard-replit--mav2326.replit.app/)
I also just created my Contra account a few weeks ago, so I’m really excited to be here, share what I’m building, and see where this journey goes. ✨
Would love to hear what you think!
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A multi-model AI support system combining fine-tuned LLMs, RAG pipelines, and intelligent routing to handle enterprise customer queries autonomously.
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