• 

  best frontend

Inspiration

Medicine costs can create a significant burden for patients and families. People often struggle to compare medicine prices across brands, understand affordable options, and make informed decisions. We wanted to build a solution that makes medicine cost information easier to access and helps people explore potential savings without compromising safety.

What it does

MEDICOST AI is an AI-powered medicine cost intelligence platform designed to help users explore medicine prices and affordable options. It allows users to search a medicine catalogue, compare listed prices across brands and packs, identify potential savings, and interact with an AI assistant for medicine-related information.

The platform is designed with safety in mind. It does not replace doctors or pharmacists, and users should consult qualified healthcare professionals before changing prescribed medicines.

How we built it

We built MEDICOST AI using a modular software architecture with a focus on usability, extensibility, and responsible AI integration. The project combines a medicine catalogue, structured product and pricing data, backend APIs, and an AI-agent workflow for handling medicine-related queries.

We also prepared a curated dataset of medicine and brand-product listings with source references. The prototype uses this data to demonstrate medicine search and price comparison. Listed prices are dataset snapshots and may differ from current pharmacy prices.

Challenges we ran into

One of our main challenges was organizing medicine information across different brands and pack sizes while keeping comparisons understandable. We also had to consider the risks of AI-generated healthcare responses and distinguish general medicine information from clinical advice.

Another challenge was designing the system so that future integrations—such as verified pricing sources, prescription document processing, and pharmacy availability—can be added without rebuilding the core platform.

Accomplishments that we're proud of

• Developed a working prototype concept for medicine search and price comparison.
• Structured medicine and brand-product data with source references.
• Designed an AI-agent workflow for medicine-related queries.
• Focused on affordability, transparency, and safety-conscious recommendations.
• Established a modular foundation for future integrations and improvements.

What we learned

We learned that healthcare technology requires more than a useful interface. Reliable data, transparent sources, responsible AI behavior, and clear limitations are equally important. We also learned how modular architecture and structured datasets can help turn an idea into a demonstrable software prototype.

What's next for MEDICOST AI

Our next steps are to integrate verified and regularly updated pricing sources, improve medicine-name normalization, expand the curated dataset, and strengthen testing. We also plan to explore prescription OCR, pharmacy availability, secure user accounts, and integrations with relevant healthcare systems.

Our long-term vision is to make medicine-cost information more transparent and accessible while keeping patient safety at the center of the experience.

Built With

• ai
• artificial
• css
• express.js
• generative
• html
• intelligence
• javascript
• json
• node.js
• rest