Building HemoConnect: An AI-Powered Companion for Thalassemia Management

DaKaufeeBoii — Sun, 12 Jul 2026 13:30:39 +0000

When managing a chronic condition like Thalassemia, patients and their caregivers often face a fragmented healthcare experience. From tracking down blood availability in emergencies to decoding complex medical reports, the cognitive load is immense.

Our team, TechMonsters, is set out to bridge this gap.

The result is HemoConnect—a unified, AI-powered platform designed to provide real-time resources, personalized health insights, and a supportive community. Here is a deep dive into how we built it, the tech we used, and the hurdles we overcame.

The Problem we Solved

Thalassemia management requires continuous, lifelong care, primarily centered around blood transfusions and monitoring iron levels. We identified three major pain points in the current ecosystem:

Emergency Blood Sourcing: Finding compatible blood during shortages is highly stressful and relies heavily on disjointed social media posts or calling multiple blood banks.
Medical Jargon: Lab reports (like ferritin levels or hemoglobin counts) are difficult for the average patient to interpret contextually.
Isolation: Patients lack a centralized, safe space to connect, share experiences, and access verified care directories.

HemoConnect solves this by acting as a single hub featuring a real-time Blood Order system, a Care Directory, a Community forum, and an AI-driven Report Analysis & Chatbot Assistant.

Tech Stack & Partner Tracks

To build a responsive, scalable, and intelligent platform within a strict time crunch, we carefully selected a modern full-stack and AI architecture.

Frontend: React. We needed a snappy, interactive user interface for the main Dashboard and seamless navigation between the community and care tools.
Backend & Database: Supabase / Firebase. This handled our authentication and the real-time database syncing required for the live Blood Order feature and Community forums.
AI & Machine Learning: Python. We built a custom Retrieval-Augmented Generation (RAG) system to power the context-aware Chatbot Assistant and the Report Analysis engine.
Partner Tracks used: Made using Base44 Planning on using Sarvam AI for Voice Chat features (WIP).

Implementation Deep Dive

The core of HemoConnect lies in how its features interact to create a holistic user experience.

The Context-Aware Chatbot & Report Analysis
The standout feature of HemoConnect is its intelligence. Instead of a generic bot, we implemented a sophisticated RAG architecture. Users can upload their latest medical reports, and the Report Analysis tool processes the data, breaking down complex metrics into understandable insights. The Chatbot Assistant is highly context-aware, meaning it remembers the user's specific health data from the reports and answers follow-up questions accurately, acting as an always-on digital health companion.
Real-Time Blood Ordering
Time is of the essence when a transfusion is needed. We built a real-time pipeline where the Blood Order page syncs directly with our backend database. This allows users to request specific blood types and see availability instantly, drastically reducing the time spent searching during critical moments.
Community & Care Directory
Health is as much about mental support as it is physical. The Community page provides a forum-like experience for users to connect. Alongside this, the Care Directory acts as a verified list of specialists, clinics, and resources tailored specifically for Thalassemia care.

Challenges we faced

Building a health-tech MVP in a highly compressed timeframe brought several significant challenges:

Preventing AI Hallucinations in Healthcare Data: When dealing with medical reports, the AI cannot afford to guess. Fine-tuning our RAG system to strictly anchor its responses to the provided medical context (and safely stating when it didn't know an answer) required intensive prompt engineering and data structuring.
Real-Time Data Syncing: Ensuring that the Blood Order feature updated concurrently for all users without lag or database locking issues was tricky. We had to carefully optimize our backend listeners to handle concurrent read/write requests efficiently.
UI/UX for Accessibility: Designing a dashboard that houses complex AI tools, community forums, and emergency features without overwhelming the user took several iterations. We focused heavily on a clean, card-based layout to keep the cognitive load as low as possible.

Conclusion & Future Scope

Building HemoConnect was an incredible sprint of coding, debugging, and learning. It reinforced how powerful modern web frameworks and context-aware AI can be when directed at real-world healthcare problems.

Looking forward, we want to expand HemoConnect by integrating direct APIs with local blood banks for automated inventory tracking and adding predictive analytics to warn users of potential iron overload based on their historical report data.

Acknowledgements & HackHazards '26

This project was built as part of HackHazards’26, beautifully organized by Namespace. Competing and building under pressure is always an incredible experience, but it wouldn't be possible without the right backing.

We want to extend a massive thank you to the event sponsors for their support and for providing the developer tools that powered our build. A very special shoutout to Base 44 for their incredible backing, along with huge thanks to Expo, Sarvam, and Neo4j for helping make this event and our project a reality!

Check out the live project here.