You know how everyone talks about "data-driven decisions" but nobody actually knows where to start? So what I do is build tools that bridge that gap β from customer churn prediction models to AI-powered analytics. In fact, I've spent 10+ years in customer analytics and now build the AI tools I wish I had back then.
π οΈ Stack: AI: Claude Code, MiMo Desktop, Hermes Agent Desktop, Codex | Data: Python, R, SQL | Infra: Firebase, Render, Supabase, Vercel
πΌ Consulting: Founder at datafying, helping businesses with customer analytics (churn prediction, segmentation) and turning data into decisions that elevate customer experience
π¨βπ« Mentoring: 20+ emerging data professionals to become strategic business partners who drive decisions with data
π¨ Currently: AI voice & music tools, plus agentic workflows for customer analytics
| App | What it is | Demo |
|---|---|---|
| hum | AI music generator β chat, docs, repos, or YouTube β songs | live |
| hanna | Chrome TTS extension β karaoke highlighting, voice design & clone | repo |
| mimo-storyteller | Multi-character audio stories with karaoke playback | live |
| mimo-reader | Browser TTS β 100+ voices, design & clone, export WAV/MP3 | live |
| puff | Quit-smoking PWA β hold + blow, streaks, Firebase sync | live |
| noise-monitor | PWA noise monitor β live waveform + spoken alerts | live |
R Β· Python Β· SQL β churn, marketing response, VoC, model explainability
| Work | Business question |
|---|---|
| tidymodels | Who will churn? β Tree vs RF vs XGBoost |
| predict-marketing-response-with-xgboost | Who will respond to a campaign? |
| linear-regression-in-r | Where should ad spend go? |
| review-data-using-SVC | What are customers saying? (review NLP) |
| model-studio | Why did the model decide that? (explainability) |
| persona | Synthetic customer interviews in 15 mins |
More ML/stats notebooks (Prophet, AutoKeras, GLM, β¦) β repos
- sql-for-everyone β Interactive SQL for non-technical business people Β· live
- ai-for-kids β AI course for ages 5β7 Β· live
- melbourne-property-intelligence β LLM property market intel β RAG, FastAPI, Streamlit, Docker
- property-auction-dataviz β Melbourne auctions mapped β scrape, clean, geocode, Leaflet




