Hi Zoë! Yes — I’ll share a short demo video soon.
The project is called GeoAlerta AI, an applied AI platform designed for emerging cities. It integrates geospatial intelligence, climate data, and predictive analytics to identify flood-risk areas and support faster public...
I've built a new mobile AI assistant that brings chat, text and image generation, voice input and document analysis into one app.
It have Smart Chat, Text Creator, Image Create, Voice Input, plus PDF Scanner, Photo Analyze, Social Content and Prompt Ideas, filtered by category.
Almost everything AI can do, just in one place.
Building AI for healthcare leaves zero room for error.
I’m currently collaborating with an incredible team on Raphald AI, a medical detection application. Building the systems for a project with stakes this high is a massive reminder that the underlying backend architecture matters just as much as the machine learning model itself.
When integrating diagnostic AI, your API endpoints cannot drop requests, and your database workflows demand absolute integrity. You aren't just passing JSON payloads; you are handling critical, real-time workflows where stability is non-negotiable.
Engineering these systems continues to shape my approach to building robust Python backends. If you are developing a product that requires reliable AI integration or rock-solid FastAPI infrastructure, check out the newly updated services on my profile. Let's build something that works when it counts.
Tatiana Beauty is a booking and operations system built for a real makeup artist and educator in Chișinău, Moldova.
Most customer inquiries start on Instagram or WhatsApp with questions like “Are you free Saturday?”, “How much is makeup?” or “Can I book makeup and hair?”
What looks like a simple question creates repetitive work: checking the calendar, proposing times, waiting for a reply, confirming the appointment, sending reminders, handling rescheduling and trying to refill cancelled slots.
Tatiana Beauty moves that coordination into one workflow.
Customers see real availability and request an appointment themselves. Tatiana keeps control with final booking approval, while confirmations, reminders and customer self-service handle the routine follow-up.
When a time becomes available, the waitlist can automatically find the oldest compatible customer, reserve the slot temporarily and offer it to them. If accepted, it converts safely into a normal booking request.
The system also coordinates combined Makeup + Hair appointments across Tatiana and Diana’s independent calendars.
For Tatiana, the private studio brings together appointments, manual Instagram/WhatsApp bookings, working hours, blocked time, customers, waitlist activity and operational impact.