Inspiration

In India, thousands of thalassemia patients rely on regular blood transfusions to survive. Yet, they often face delays, mismatched donors, and lack of timely support — not because of unwillingness to help, but due to poor coordination. We were inspired to build PulseBridge to connect patients, donors, and NGOs through the power of AI — to save lives by improving communication, prediction, and care logistics.

What it does

PulseBridge is an AI-powered platform that:

Predicts future blood demand using regional data

Matches donors to patients based on blood type, location, and timing

Provides NGOs with a dashboard to manage blood donation, outreach, and stock updates It acts as a smart assistant that connects people and technology to ensure no patient is left waiting for blood.

How we built it

We used the following approach and tools:

Designed the idea flow and architecture on paper first

Used Python for the AI prediction model (using dummy demand data)

Created a prototype dashboard using Streamlit (or say Figma if you only did UI mockup)

Added donor–patient matching logic using simple ML rules and filters

Wrote documentation and pitch with a focus on user impact and simplicity

Challenges we ran into

Finding real-time medical/donor datasets was difficult

Matching donor location data with patient urgency was tricky

Balancing AI predictions with user-friendly visuals took time

Since we are beginners, choosing the right tech stack and prioritizing features was a learning curve

Accomplishments that we're proud of

We created a complete concept that addresses a real-world health challenge

Designed a clean and usable donor-patient matching system

Learned how AI can directly impact healthcare in meaningful ways

Developed a solution that could genuinely assist NGOs and save lives

What we learned

How to approach a real-world problem with AI-based thinking

Basics of AI/ML prediction using Python

How to break a large idea into smaller, buildable components

The importance of human-centered design in healthcare tech

What's next for PulseBridge

Integrate with e-RaktKosh or blood banks for real-time data

Add a donor chatbot assistant to answer FAQs and book appointments

Expand the prediction model using real hospital demand datasets

Partner with NGOs to test the dashboard in actual thalassemia clinics

Improve the UX for mobile access in rural areas.

Built With

• colab
• figma
• google
• pandas
• python
• scikit-learn
• streamlit