Oleksandr Korol

Engineering case study

Delivering a personalized digital health and lifestyle platform

The platform connected users with medical experts, placed personalized lifestyle recommendations into their calendars, and helped them track progress over time.

Mental health/lifestyle platform

This case study describes commercial work at a level suitable for public sharing. Client-identifying and confidential implementation details are intentionally omitted.

01

The challenge

The product needed to coordinate expert communication, recommendations, calendars, progress feedback, payments, and multilingual content while keeping the experience approachable for end users.

02

Engineering approach

  1. Combined Django REST Framework and FastAPI services with a React and Material UI interface.
  2. Worked with an integration stack that included Google Calendar, Google Translate, Twilio, and Stripe.
  3. Used a recorded data and background-work stack that included NumPy, Pandas, Celery, SQS, and Redis.
  4. Included unit testing, Pytest, and Locust in the project’s quality-tool inventory.

03

What the product enabled

  • Connections between users and medical experts
  • Personalized recommendations delivered through calendars
  • Progress visualization and achievement feedback
  • Communication, payment, and translation integrations

04

Delivered outcomes

  • Unified recommendations, scheduling, communication, and progress tracking in one product.
  • Created an integration-rich foundation for personalized lifestyle workflows.
  • Included automated testing and load-testing tools in the delivery stack.

These outcomes summarize the available project record; no client metrics have been inferred.

05

Technology used

  • Django
  • DRF
  • FastAPI
  • Pydantic
  • React
  • Material UI
  • Twilio
  • Stripe
  • Google Translate API
  • Google Calendar API
  • NumPy
  • Pandas
  • Locust
  • Pre-commit
  • Pytest
  • Unit Testing
  • AWS EC2
  • AWS SQS
  • Celery
  • Nginx
  • Redis
  • PostgreSQL

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