STAGES OF DEVELOPMENT
We came up with and shaped the concept of Aintermed as an AI platform for medical students and doctors. Defined goals: AI assistant access, knowledge base, subscriptions, user account. Planned architecture and development phases.
We built the first interface from scratch: design system, dark theme, simple UX. Assembled an MVP with core features: AI chat, section structure, knowledge base, and basic analytics.
We launched the platform to production in 12 weeks. Started collecting user feedback, tracked behavior and growth points, implemented analytics and A/B testing.
Redesigned the UI after analyzing user behavior. Improved card views, readability, and mobile experience. Added payment plans, subscription, and registration system.
Integrated more powerful LLM models and updated the query logic. Performed a full redesign with a new visual style. Increased performance, added sections, and improved stability.
CHALLENGES AND HOW WE SOLVED THEM
Medical knowledge is vast — and constantly evolving. Students struggle to keep up with scattered, outdated materials and lack real-time guidance.
We built an AI assistant that stays updated with the latest clinical guidelines and literature, delivering relevant answers in seconds — always in context, always up to date.
Clinical reasoning is hard to practice outside real hospitals. Traditional textbooks can’t simulate decision-making or adaptive thinking.
Our AI creates realistic, interactive clinical scenarios that adapt to the learner’s choices — helping students train critical thinking like never before.
Language models often ignore the importance of evidence. In medicine, that’s not just a bug — it’s a risk.
We trained our model to cite sources, link to guidelines, and prioritize evidence-based answers — building trust, transparency, and accountability into every response.
