Designing Gyan AI:
AI-Powered Patient Case Simulator
Bringing textbook case studies to life with AI feedback and real-world confidence.
PROJECT TIMELINE
6-week Sprint
January 2025 – March 2025
MY ROLE & SCOPE
KEY IMPACT
TEAMMATES
PROBLEM
Traditional Q-banks teach you to pick from choices, making med students graduate nervous about their clinical skills
Medical school students spend hours on static case texts or peer drills and still lack the real-time, explainable feedback they need to build diagnostic and bedside manner confidence. This leads to inefficient study sessions, low practice volume, and, most importantly, results in graduates who feel underprepared for live patient encounters at hospitals.
DESIGN FOCUS & DIRECTION
How might we use AI to help medical students practice clinical reasoning and communication skills in a safe, feedback-driven environment?
OPPORTUNITY & SOLUTION
Gyan AI: Master diagnosis with an
interactive AI patient and immediate feedback
Gyan AI delivers an interactive, branching patient-case simulator that explains its reasoning at each step, so learners can practice autonomously and understand why they made (or avoided) mistakes.
AI-Patient Interaction workflow
With Gyan AI, users can easily practice their clinical skills with AI patient sims.
FEATURE: DASHBOARD + CUSTOM PRACTICE MODES
Dashboard for targeted practice
The dashboard surfaces accuracy, time, and recent cases in one place. Students can quickly resume an in-progress case or start a new one by topic and difficulty, instead of hunting through a list of scenarios.
FEATURE: CHATTING WITH AI PATIENT
Single-screen consult room
that mirrors real visits
The consult screen keeps video, patient data, notes, and test orders side by side. Learners talk to the virtual patient, order investigations, and then commit to a working diagnosis with written reasoning, all in a single view.
FEATURE: SINGLE FEEDBACK LOOP
Structured feedback
and reflection
After each case, Gyan shows accuracy and time, prompts the learner to reflect, and then breaks performance down by stage. Students see where they did well, where they missed cues, and can move on to the next case with a clear takeaway.
RESEARCH & SCOPING
What did talking to 20+ medical students
and analyzing 300+ data points tells us…
Before designing, I led foundational research to understand the landscape of medical education and define a viable product opportunity. I interviewed 20 medical students and benchmarked over 15 indirect and direct competitors. This process revealed four critical insights that became the foundation for Gyan AI.
KEY INSIGHT 1
The Confidence Gap
Students had strong theoretical knowledge but lacked conversational confidence. They needed a safe space to practice patient interaction skills.
KEY INSIGHT 2
The Scalability Gap
Competitors offered either basic quizzes or costly, non-scalable human simulations, highlighting a market need for a scalable AI-powered training tool.
KEY INSIGHT 3
The Actionable Feedback Gap
The biggest need was actionable feedback, as students required clarity on their answers, making our AI feedback system essential for the MVP.
KEY INSIGHT 4
The Need for a "Safe Space to Fail"
Students feared being wrong and harming real patients. The product's key feature was to create a safe space for learning from mistakes without consequences.
ITERATE ITERATE ITERATE?
Some pictures of our product evolution…
The product has started from the idea of making medical textbooks easy to grasp, to making textbook case studies come to life.
