Nicolás Ramírez Borches
MBA candidate at Chicago Booth. Previously led Product and Operations at a YC-backed fintech.
The projects below are products I designed and launched during my MBA, each one started from a real problem I wanted to solve.
SpendLens
Personal useAI-powered spending analysis and net worth tracking.
What it is
A personal finance tracker that consolidates spending and investments in one dashboard, with AI-powered categorization that learns from your behavior over time.
Why
Managing personal finances across multiple banks and asset types means constantly context-switching between apps, none of which talk to each other. I wanted one place to see the full picture.
How it works
Upload your bank statements and the app automatically categorizes each transaction. When it's uncertain, it asks you, and remembers your answer for next time. Add your investment holdings to get a unified view of where your finances stand.
Reduse
Booth Start-up CompetitionSmart pantry & meal planner to reduce food waste.
What it is
A smart digital pantry that helps you track what you have, know what's expiring, and actually use it before it goes to waste.
Why
The average household throws away nearly a third of the food it buys. Most of that waste is invisible, we forget what's in the fridge, misjudge expiration dates, and over-buy. I wanted to see if a better interface could change that behavior.
How it works
Log items when you buy them and the app tracks expiration dates, surfacing timely reminders before things go bad. The Recipe module suggests meals based on what you already have, so using up your pantry becomes the path of least resistance. Built and piloted with 30 users as part of a Booth VC pitch competition.
Condit.io
Class project & classmate start-up ideaStore compliance platform with AI photo analysis.
What it is
An AI-powered CRM for visual compliance: a single place where owners and store managers align on how locations should look, and where deviations get surfaced automatically.
Why
For multi-location businesses, retail chains, franchises, hospitality groups, maintaining consistent visual standards across every store is a real operational problem. District managers rely on manual walkthroughs and photo threads. There's no systematic way to catch issues early or hold locations accountable.
How it works
Store managers receive compliance requests and upload photos of specific sections. An AI vision model analyzes each image against defined standards and flags potential issues. Owners see a dashboard summarizing compliance across all locations, with specific items to review and approve.