StudyMed

StudyMed is a self-reported educational platform for medical students that aims to consolidate fragmented learning tools into one integrated environment. The platform includes interactive courses, clinical simulations, research collaboration features, and academic writing support, all built with AI assistance. It is described as a web application using Next.js, React, TypeScript, and Supabase, deployed on Vercel.

The description states that StudyMed was built by two founders (Dorian Komar, Igor Komar) over a hackathon period, using GPT 5.6 and Codex for development assistance. The platform is positioned to support the full learning path from understanding topics through courses, applying knowledge via games and simulations, finding research partners, and writing academic papers.

Key commercial due-diligence questions:

• What is the actual product capability and user experience?
• How does StudyMed differentiate from existing educational tools?
• Is there evidence of real student adoption or feedback?
• What are the technical and data security limitations?

The most important open question: Is there any evidence that medical students actually use this platform, or that it solves a genuine problem beyond the authors' assumptions?

The description states StudyMed is a web application built with Next.js, React, TypeScript, Tailwind CSS, and Supabase, deployed on Vercel. It includes features such as:

• Free, topic-based courses
• Interactive learning games (ECG Reader, Lab Reader)
• Virtual clinical decision making simulation (YourClinic)
• Research collaboration space (Research Partners)
• Academic writing workspace (YourPaper)
• AI-powered explanation tool (MedGenius)

The platform is described as being built with GPT 5.6 and Codex for development assistance, with the authors claiming these tools were used throughout the build process.

The description states that StudyMed started as a simple idea for an ECG learning game but evolved into a broader educational platform covering clinical training, academic writing, and research collaboration. The positioning is described as being "designed around how medical learning actually happens" rather than another quiz app.

The authors claim the platform supports "the full path: understanding a topic through courses, applying that knowledge through games and the virtual clinic, going deeper by finding research partners, and finally writing original academic papers."

The description states StudyMed is designed for medical students. The authors note that while studying and helping fellow students, they observed that exam and career preparation is scattered across many disconnected sources.

The platform is described as being built "strictly for educational purposes" with no real patient data or diagnoses.

Not evidenced. The description does not contain any information about pricing models, monetization strategies, or business model assumptions.

The platform is described as a web application built with:

• Next.js, React, TypeScript, Tailwind CSS
• Supabase for database and authentication
• Deployed on Vercel
• Built modularly so each feature could grow independently while sharing account system and interface language

The authors state they used GPT 5.6 and Codex throughout the build process, including:

• Choosing technology stack
• Shaping communication with Codex
• Turning product needs into implementation plans
• Building frontend components and backend logic
• Debugging issues using logs and targeted tests
• Preparing for release through configuration, testing, and documentation

Not evidenced. The description does not contain any information about user adoption, customer base, revenue, or usage metrics.

Not evidenced. The description does not contain any information about existing competitors or market positioning relative to other educational platforms for medical students.

• The platform is described as being built by two people over a hackathon period
• No evidence of actual user adoption or feedback
• The platform is described as "strictly for educational purposes" with no real patient data, which may limit its practical utility
• The authors note they never treated AI-generated code as automatically correct, suggesting potential quality control issues
• The project was submitted to a hackathon, indicating early-stage development

1. What specific problems do medical students face that StudyMed solves?
2. How many actual medical students have used this platform and what feedback have they provided?
3. What is the current development status of the platform beyond the hackathon version?
4. How does StudyMed plan to differentiate itself from existing educational tools in the market?
5. What are the technical limitations or scalability concerns with the current architecture?
6. How will the platform handle data security and privacy for educational content?