Projects

What I've Built

Projects documented with architecture decisions, stack rationale, tradeoffs, and what I'd do differently.


Prototype

HR Policy Knowledge Copilot

Enterprise RAG · HR & Policy Management

A working RAG prototype that lets employees ask plain-English questions about company policies and get cited answers from source documents. Built specifically to show the data preparation problem most enterprise AI projects fail at — and how to solve it.

RAG N8N OpenAI Claude Supabase Netlify

Stack

N8N
Orchestration & chunking pipeline
OpenAI
Embeddings
Claude
Answer generation
Supabase
Vector storage (pgvector)
Netlify
Frontend hosting
Live

Gosona.ai — AI Voice Receptionist

Voice AI · Service Business Automation

An AI voice receptionist that answers every call, books consultations, and captures leads 24/7 for service businesses. Handles full conversation flow, qualification, and calendar booking without human involvement.

Voice AI Retell AI Claude OpenAI Supabase Netlify

Stack

Retell AI
Voice agent platform
Claude
Conversation & reasoning
OpenAI
Speech-to-text
Cal.com
Calendar booking API
Supabase
Database & webhooks
Netlify
Deployment
Live

PayoffHub.com — Debt Payoff Platform

Personal Finance · Consumer Product

A personal finance platform built to help everyday people get out of debt through education, calculators, and community. Built end-to-end as a real deployed product.

OpenAI Claude N8N Cloudflare Netlify

Stack

OpenAI
Content & recommendations
Claude
Financial guidance copy
N8N
Automation workflows
Sendlayer
Transactional email
Cloudflare
Edge & security
Netlify
Deployment
Live

Local LLM Pipeline — Mac Mini

Local AI Infrastructure · Privacy-First RAG

A fully local RAG pipeline running on an M4 Mac Mini. No external API, no data leaving the machine. Built to understand what running AI on real hardware actually requires: the memory constraints, quantization tradeoffs, and architectural decisions that cloud-based development never forces you to confront.

Local AI Ollama Llama 3.1 ChromaDB n8n Docker

Stack

Ollama
Native inference engine (M4 GPU)
Llama 3.1 8B
Q4_K_M quantization — 4.7GB active
nomic-embed-text
Local embeddings
ChromaDB
Vector storage — persistent SSD
n8n
Orchestration & pipeline automation
Docker
Sandboxed infra (3GB hard cap)