Automate Resident Billing: Python Solution for Apartment Management

Automate Resident Billing: Python Solution for Apartment ManagementAutomate Resident Billing: Python Solution for Apartment Management

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Mar Cabrera

• 19h

A 36-unit apartment building in Buenos Aires needed to stop chasing residents for payments over WhatsApp.

I built a system that automatically sends each resident their expenses, what they owe, and when it's due. Clear numbers, on time, no phone calls.

The building administrators went from spending hours every month on this to spending zero.

Python · Django · Gmail API · PostgreSQL

Automation Engineering Backend Development Business Workflow Automation Django PostgreSQL Python

Blessing Uwah

• Mar 5

You don’t really understand your money until you see where it’s quietly disappearing. A few days ago I shared the onboarding screens for Budgit, a personal budget tracker designed to help users see their spending clearly. Today I worked on the home screen, the screen users return to every day. The quick balance check before making a purchase. The silent “hmm” when expenses are higher than expected. It’s not just about tracking numbers, but helping users feel in control every single time they open the app. Designing this part challenged me to think deeper: How do you present financial information without making it feel heavy? How do you simplify data without oversimplifying reality? Because when people can clearly see their money, they make better decisions, not out of fear, but from confidence.

uiuxdesigner fintechapp budgettracker UX Design UX Research Figma

Khunsa ✪‌

• Mar 6

Good job

Tanya Omelchuk

• Mar 5

Calendar-Driven SMS Reminder Automation.

Built an automation that monitors Google Calendar events, retrieves associated contact details from Google Contacts, and sends SMS reminders through Telnyx. Uses iteration logic to process events and ensure messages are sent only when valid phone numbers are present.

Business Workflow Automation Make Twilio Google Calendar

ANIMESH SINGH

• Mar 4

Problem: Many organizations still process invoices manually by reading PDF documents and entering key details (invoice number, vendor, amount, etc.) into systems. This process is slow, error-prone, and difficult to scale, and it also makes it harder to detect duplicate invoices or incorrect totals.

Solution: This project builds an automated invoice processing pipeline that converts uploaded invoice PDFs into structured data. It uses OCR to extract text, LLMs to identify invoice fields, validation checks to ensure correctness, and Kafka-based event streaming to manage the processing pipeline. The extracted data is stored in PostgreSQL and visualized through a dashboard, enabling faster, scalable, and more reliable invoice processing.

AI Engineer Apache Airflow Kafka Python Data Engineering

Abhiram Tinguria

• Mar 4

Very real problem. Manual invoice processing is still surprisingly common and becomes a huge bottleneck as companies scale. Automating extraction and validation with AI can save a lot of operational time and reduce errors significantly.