Victor Colombo

A working portfolio of software.

Product thinking meets AI-assisted building.

As President and Managing Partner of Fiat Growth, a fintech-native growth consultancy serving venture-backed fintechs, I lead a team committed to helping our clients scale their businesses.

My career has been grounded in clients and customers. At American Express I worked directly on new consumer card launches, helped build and ship new features and benefits, and partnered hand-in-hand with technology teams and merchant partners to build and scale entirely new forms of card distribution partnerships.

That same instinct drives the work below. Though far from an engineer, I've built working software for both professional and personal use by deeply understanding a need and thinking systematically about how to solve it, using AI tools to design, build, and ship real products.

When I'm not building, I'm appreciating life in Brooklyn with my wife and kids, a good espresso or Nebbiolo, and probably overthinking my fantasy basketball draft.

See what I've built Get in touch
Victor Colombo
Professional products

Tools I built for work

Two platforms built for Fiat Growth: one that accelerates the client work, and one that runs the business behind it.

Fiat Studio

A strategist-led platform that uses AI to accelerate our go-to-market work.

In Use
The problem

The fintechs we work with need to move fast, and eight years and 200+ clients have given us deep experience and a large body of proprietary data that mostly lived in people's heads.

What I built

A first working iteration that keeps our strategists in the driver's seat and uses AI to accelerate the work they lead. A strategist moves a client through a guided flow — competitive intel, ICPs, messaging, creative, lifecycle — with AI agents grounded in our fintech benchmarks so the output reflects Fiat's methodology, not generic AI. It's now in active development as I build it out with others across the team.

Key functionality
  • Strategist-led, AI-accelerated flow — each module feeds the next, keeping the GTM plan coherent as AI compresses each step.
  • Grounded in proprietary data — outputs draw on Fiat's fintech benchmarks and eight years of client insights, not the model's imagination.
  • Ad Intelligence — agents pull and analyze competitor ads from the Meta Ad Library far faster than a manual review.
Tools / stack
Next.js 14ReactTypeScriptSupabase / PostgresAnthropic ClaudePineconeTailwindVercel
Click to enlarge Fiat Studio — Ideal Customer Profiles

Fiat Ops Dashboard

The command center that runs the business side of the agency — revenue, capacity, pipeline, and client health in one live view.

In Use
The problem

Leadership was running the business across scattered spreadsheets, Salesforce, and PDF contracts, with no single view of revenue, team capacity, or the health of the client portfolio.

What I built

An internal web app that unifies Google Sheets, Salesforce, and signed contracts into one real-time operating picture: revenue by client and service line, who's over- or under-booked, pipeline, margins, renewals, and client health, all role-gated. A Postgres backend handles ingestion, forecasting, and commission math.

Key functionality
  • AI contract ingestion — on Closed Won, AI reads the signed PDF and extracts client, dates, value, and billing terms into a review queue, no manual entry.
  • Live profitability scoping — as you staff a client, see billing vs. cost-to-deliver vs. gross margin in real time, plus each person's capacity across clients.
  • Forecasted revenue — blends signed revenue with the Salesforce pipeline, weighted by how likely each deal is to close.
Tools / stack
ReactViteSupabase (Postgres + Edge Functions)Anthropic ClaudeGoogle Sheets / DocsSalesforceQuickBooksVercel
Screenshots coming
Hobby products

Apps I built for my life

Real, deployed apps I use at home.

Meal Planning App

Swipe your way to a week of dinners in seconds.

Live
The problem

"What's for dinner?" is a nightly tax on mental energy, and coordinating meals across a household adds friction right when everyone's busiest.

What I built

You build the week as a stack of swipeable recipe cards — keep the dinners you want, swap the rest, and it re-deals around your picks (no back-to-back starches, moods like "quick" or "no oven"). One tap pushes the plan to your calendar and a grocery list. Rate dishes and it sharpens to your taste over time.

Tools / stack
Next.js 16React 19SupabaseClaudeFramer Motion
Click to enlarge
Meal Planning — new plan

Wine Tracking App

Snap a label, catalog the bottle, know when to drink it.

Live
The problem

A wine collection's tasting notes, ratings, and drinking windows usually live in scattered notes or a spreadsheet — so you never quite know what's ready to open.

What I built

A single-user PWA where you photograph a label and Claude vision auto-extracts producer, vintage, and varietal. It tracks drinking windows, ratings, and storage locations, and a taste-insights view surfaces the patterns across a collection — producers, countries, varietals, and regions. So far it has catalogued over 600 wines.

Tools / stack
Next.js 16React 19SupabaseClaude VisionVercel
Click to enlarge
Wine cellar list

Kids Stickers App

Track and celebrate kids' good behavior — no spreadsheet required.

Live
The problem

Rewarding kids for chores and good behavior needs to feel celebratory, not clerical.

What I built

A mobile-first PWA parents run on their phone with their kids. Awarding a sticker fires confetti and haptics; stickers pile into playful collages, and milestones, streaks, and redeemable rewards keep it fun. Built direct-to-production and in active family use.

Tools / stack
Next.js 16React 19Tailwind v4Framer MotionSupabaseVercel
Click to enlarge
Kids stickers app
In development

Active development

Projects I'm actively building out and pushing toward broader use.

Fantasy Basketball Draft-Day Sidekick

Plan the perfect draft, then run it live.

In Use
The problem

Auction drafts demand dozens of judgment calls under time pressure, yet most tools offer vague advice instead of real numbers — and none help you walk in with a coherent plan in the first place.

What I built

Two tools in one: a pre-draft planner and a live draft-day cockpit. A projection pipeline, backtested across past seasons, builds an optimal target roster with fallbacks at every position, and a Monte Carlo simulation pressure-tests it across thousands of scenarios. On draft day it runs live, updating predicted prices, category strategy, and position scarcity as picks come off the board.

Tools / stack
Next.js 16React 19ZustandSupabasePython / PandasVercel
Click to enlarge Fantasy basketball draft board

Brooklyn Real Estate Assessment Tool

Broker-grade comps, built for buyers and sellers — not brokers.

In Use
The problem

Finding the right clearing price depends on high-quality comparable-sales data, usually accessed through a broker. The few tools that exist are built for brokers, not homeowners and buyers.

What I built

A tool focused on one narrow slice of Brooklyn, going deep rather than wide for genuinely precise comps. A five-stage pipeline ingests a StreetEasy listing, reads floor plans and photos with vision models, then layers in the factors that actually move value here: school zones, distance to the subway, layout, and the specific block. NYC PLUTO records enrich every assessment.

Tools / stack
Python 3.11SupabaseClaude VisionReact / ViteNYC PLUTO API
Private tool
Screenshots coming