MIND automates medical billing coding for French
physicians. The system reads clinical notes and
suggests the correct CCAM codes in real time —
eliminating manual lookup and reducing billing errors.
Built solo from scratch:
— NLP pipeline for clinical note analysis
— Secure architecture for sensitive medical data
— Go-to-market strategy targeting independent
practitioners
Stack: Python, NLP, cloud-native, HIPAA & GDPR-compliant
data architecture.
Role: Sole founder — product, engineering,
and distribution.
An AI workflow that reads every incoming email, sorts it into 6 categories, and takes the right action automatically.
The problem: businesses lose time and leads because customer emails are mixed with promotions, job alerts, and security emails.
What I built:
Gmail Trigger that picks up each new email
AI Text Classifier (Google Gemini) with 6 categories: Security Alert, Promotions, Jobs, Personal, Payments, and Client Inquiries
Automatic Gmail labels for every category
Google Sheets log for jobs, leads, and payments
AI information extraction for client emails (name, phone, service, budget)
AI-written reply drafts for client emails, saved as drafts so a person approves every reply
Instant Discord alerts for security, payment, and client emails
Tools: n8n, Google Gemini, Gmail, Google Sheets, Discord
This project is a working demo built on my own inbox. The same system can be adapted to any business email, such as travel agencies, event venues, stores, recruiters, and consultants.
A small experiment with a more cinematic AI video.
30 seconds, one story, one prompt: a girl crosses a ruined city to find medicine for her younger sister. The ending doesn’t go exactly as planned.
The goal here was not just action, but:
realistic cinematography, tension, clear storytelling, and an emotional ending.
What do you think about this format?
Drop in any logo and it fills up like liquid while a rolling counter climbs to 100%, then the logo pops and a check badge lands. It is made for SaaS upload, export and onboarding screens, where a generic spinner would normally sit.
To rebrand it, replace one logo image, retype three texts (status, done message, brand name) and change two colors. The second brand in the video (Nimbus Pay) was made through the SVGator MCP in six edits.
Named layers: logo, status-text, status-done, brand-name, progress-bar, badge-bg, percent. Motion designed in code, project built and rebranded through the SVGator MCP, then checked in the SVGator editor.