Projects that
Matter
From idea to impact, here's what I've built
Clients
150+
Projects
300+
Happy Clients
100%
Followers
100k
Product Leadership • Event Management
BREACH 2025: Gujarat's Biggest FinTech Hackathon
FUNDS RAISED
₹6.5L
PRIZE POOL
₹3.5L
UNIVERSITIES
52+
STUDENT INTERNSHIPS
10+
Concept
Conceptualized and executed PDEU's first-ever hackathon from scratch. Led cross-functional teams across marketing, operations, sponsorships, and tech to deliver a 2-day event that became the talk of Gujarat's startup ecosystem. This wasn't just an event—it was a statement. A statement that PDEU students can think big, execute flawlessly, and punch way above their weight.
WHAT I DID
Conceived the vision and pitched to university leadership.
Built and led a 15-member organizing team
Secured ₹2.5L in sponsorships (GVFL, TIME, White Carbon)
Designed participant journey, marketing funnel, and ops playbook
Managed crisis situations and real-time problem-solving during event
Impact
Set new benchmark for student-led events at PDEU
Generated ₹2L in seed funding for winning teams
Featured in local media and startup community
Data Analytics • Venture Capital/Private Equity
India FinTech Capital Intelligence (2016-2022)
FUNDING ANALYZED
$15B+
DEALS TRACKED
3,912
INVESTORS
512
CUSTOM METRICS & VISUALS
25+
CONCEPT
Built an end-to-end Power BI dashboard analyzing 7 years of Indian FinTech funding—$15B+ across 3,912 deals, 512 investors, and 61 cities. This wasn't just data visualization. This was turning 5,047 messy rows into 580 standardized records and engineering 18 custom visuals to answer: Where is FinTech capital concentrating? Which ecosystems are maturing? What happened post-peak 2021? The kind of intelligence VCs and operators pay for - I built it as a side project.
WHAT I DID
Scraped and cleaned 5,047 rows of funding data
Standardized company names, investor names, and deal types
Designed 18 interactive visuals (maps, trends, concentration charts)
Created 9 custom metrics (capital concentration index, ecosystem maturity score, etc.)
Wrote data narratives for each visual
KEY INSIGHTS
Bangalore captured 42% of all FinTech funding
Seed-stage deals dropped 67% post-2021 peak
Only 12 cities saw repeat investor activity
Product Intern • Data Analytics
Matter AERA: Telemetry Pipeline & Performance Analysis
CONCEPT
Interned at Matter Motor Works, where I cleaned a 15GB dataset of telemetry data from 12 vehicles and 38 rides—narrowing 1,077 variables down to 28 key parameters for high-impact performance analysis. Built a torque-temperature relationship metric that improved thermal performance insights across 4 critical components. Saved the team 1 week of processing time through better data pipelines.
WHAT I DID
Cleaned 15GB of raw telemetry data (Python + Pandas)
Identified 28 key parameters across thermal, performance, and battery metrics
Built torque-temperature relationship analysis
Collaborated with hardware team to implement insights
Streamlined data pipeline for future analysis
IMPACT
Improved thermal monitoring across 4 components
Enabled faster iteration on vehicle performance
Created reusable data cleaning scripts for team
Data Analytics • Business Insights
SHARK CATALYST: Data Driven Analysis of Shark Tank India
PITCHES ANALYZED
300+
INDUSTRIES
12+
INVESTORS
15+
CAPITAL INVESTED
₹500 Cr
CONCEPT
Analyzed 300+ pitches from Shark Tank India to uncover what actually drives deals. Built an interactive site with visual insights on industry trends, valuation patterns, and shark preferences. The question: Can we predict which pitches get funded based on industry, ask amount, and valuation? Turns out, YES.
WHAT I DID
Web scraped pitch data from multiple seasons
Cleaned and structured data (industry, ask, equity, sharks)
Built predictive model using logistic regression
Created interactive site with charts and insights
Wrote narrative around findings
KEY INSIGHTS
F&B and Fashion get 2.3x more deals than Tech
Ashneer had the highest deal closure rate (62%)
Sweet spot valuation: ₹2-5Cr (highest success rate)
VC/PE Analysis • Due Diligence
Certius Labs: VC Due Diligence Project
CONCEPT
Built a full, end-to-end product & go-to-market package for Certius Labs — a canonical diligence platform for high-volume seed / micro-VC screening.
The PDF contains:
• 3 market case study slides
• 2 competitor product teardowns (Affinity CRM + Carta) with UX, data, and product bets
• 1 PRD slide + linked detailed PRD
This project taught me how to convert operational pain (manual, non-reproducible diligence) into a reproducible product with measurable pilot metrics.
WHAT I DID
Market research & sizing (TAM / SAM / SOM + segmentation and unit economics)
Competitive product teardowns (Affinity CRM & Carta — feature analysis, gaps, prioritized bets)
Designed the Certius Labs PRD: canonical memo schema, deck ingestion pipeline, connectors, re-run engine, red-flag rule engine, versioning & export
Built pilot plan, pricing, unit economics, and go-to-market motions for micro-VCs / accelerators
Created a polished 9-slide investor / portfolio deck and a downloadable, exportable PRD (PDF)
FRAMEWORKS USED
TAM / SAM / SOM (market sizing)
JTBD (Jobs-to-be-done) & User Personas
SWOT & Porter’s Five Forces (competitive context)
Product teardown rubric (value, UX, data, auditability)
PRD discipline: user stories, acceptance criteria, data contracts, API surface
Unit economics & pilot metrics (CAC, ARPU, payback assumptions)
Hardware + Software • AgTech
Drone-Based Apple Orchard Management System
CONCEPT
Designed a complete agricultural drone system for apple orchard monitoring. Proposed RGB filter integration to replicate multispectral imaging, cutting hardware costs by 70% while maintaining monitoring accuracy. Achieved 50% lower cost than commercial alternatives without sacrificing functionality.
WHAT I DID
Researched commercial drone solutions (DJI Agras, senseFly)
Identified cost bottleneck: multispectral cameras
Proposed RGB filter workaround for NDVI calculation
Designed system architecture (hardware + software)
Created technical documentation and feasibility report
Product Strategy • Market Analysis
ZEPTO: Scheduled Delivery
CONCEPT
Evaluated Zepto’s instant commerce model and a practical path to improve unit economics by shifting repeat demand to scheduled deliveries. Focus: where cost savings come from, why users don’t schedule today, and a tested product approach to convert frequent shoppers to scheduled slots.
WHAT I DID
Instant vs. scheduled delivery economics
User behaviour from surveys (n=40) + interviews (n=8)
Competitive positioning & slot experience flows
KEY INSIGHTS
Awareness gap: 35% of users were unaware of scheduled delivery as an option.
Trust gap: Average on-time trust = 2.9/5; users demand guaranteed or compensated slots.
Profit lever: Scheduled deliveries can reduce delivery cost/order by 20–40% through batching and predictable routing.