I turn data into decisions —
and ideas into products.

A fueling and nutrition companion built for Type 1 diabetic cyclists — because I am one.

CrankFuel helps endurance cyclists who manage Type 1 Diabetes plan and execute their in-ride fueling: carbohydrate timing, insulin-on-board awareness, and glucose-aware nutrition strategies. It's the tool I always wished existed on long rides — built with safety as a first-class constraint, not an afterthought.

• Glucose-aware carb and fueling planning for endurance efforts
• Safety-first design — conservative defaults around insulin and lows
• Born from the intersection of two things I live: cycling and T1D

A complete refactor and modern rebuild of a law firm's web presence.

A ground-up rebuild of the Nicola Circelli Law website — modern, fast, and maintainable. Designed and shipped on a disciplined workflow: feature branches, pull requests, preview deploys, and a clean handoff. Proof that good engineering hygiene applies whether you're shipping to one client or millions.

• Full refactor to a modern, performant stack
• Branch → PR → preview-deploy → merge workflow throughout
• Backed by Supabase, deployed on Vercel

An all-in-one operations platform for home-service businesses — with an AI assistant that runs the back office.

FlowFit (codenamed FluxHammer) is a full SaaS platform for home-service trades like plumbers and HVAC techs — replacing the patchwork of spreadsheets, sticky notes, and missed calls with one system for clients, scheduling, inventory, invoicing, work orders, and reviews. Its standout is an embedded AI assistant that books jobs, drafts client records, and answers questions about the business in plain English.

• AI assistant (“Poo-Dini”) that schedules jobs and creates clients conversationally
• Kanban + calendar scheduling, invoicing, inventory, work orders, and reviews in one place
• Supabase backend with SMS via Twilio and product analytics via PostHog

A unified lakehouse combining 60+ sources into one source of truth.

I architected Paystone's data foundation — originally a data lake on AWS S3 and Redshift unifying 60+ disparate sources, then consolidated into a Databricks Lakehouse for near real-time streaming and a far stronger MLOps experience. One governed platform that every downstream model, dashboard, and AI agent now runs on.

• 60+ data sources unified into one governed platform
• Consolidated onto a Databricks Lakehouse for near real-time streaming & MLOps
• Unified data and KPIs across the entire organization
• The foundation every model, dashboard, and agent is built on

Ask the data questions in plain English — no SQL, no waiting on an analyst.

Deployed Databricks Genie on top of the lakehouse to put a natural-language interface on company data. Teams ask questions conversationally and get governed answers back in seconds — self-serve insight at the speed of a sentence, instead of a dashboard request and a two-day wait.

• Natural-language querying over the Databricks Lakehouse
• Self-serve answers without writing SQL or waiting on analysts
• Conversational AI brought to everyday business decisions

Production AI agents — from pre-sales research to RAG-powered support.

Designer and builder of Paystone's agentic AI frameworks, with two agents in production. A pre-sales research agent profiles a prospect end-to-end before every call, saving reps roughly an hour each. A technical knowledge-base agent does retrieval over Databricks Vector Search (RAG) and is served flexibly — via MCP, a Databricks App, or directly inside Salesforce chat.

• Pre-sales research agent — full prospect discovery, ~1 hour saved per call
• Technical knowledge-base retrieval (RAG) on Databricks Vector Search
• Served anywhere: MCP, a Databricks App, or Salesforce chat
• Core to Paystone's AI-first transformation

An XGBoost model predicting which customers are likely to leave a Google review.

Built a gradient-boosted (XGBoost) model that scores each customer's probability of leaving a Google review. It lets the business concentrate review-generation effort exactly where it's most likely to convert — turning behavioral signals into measurable online-reputation growth.

• XGBoost model scoring review-likelihood per customer
• Focuses review-generation effort where it actually converts
• Turns behavioral signals into reputation growth

One reporting layer to consolidate every metric across the company.

Rolled out Looker as Paystone's company-wide reporting standard — consolidating metrics that had been scattered across tools and teams into one governed layer. A single, trusted definition of every KPI, consistent across the whole organization.

• Company-wide reporting standard on Looker
• Consolidated metrics across every team into one layer
• Governed, consistent KPI definitions org-wide

An internal tool that saves hours of manual candidate screening.

Built an internal resume-screening tool to take the grind out of shortlisting candidates — saving the hiring team hours per role while keeping a human in the loop for the decisions that matter. A small, practical example of pointing ML at the boring problems.

• Automated first-pass candidate screening
• Hours saved per role, human-in-the-loop by design
• Practical ML applied to real operational friction