Building MediNova—an all-in-one AI-powered healthcare assistant—came with its fair share of hurdles. Simulating therole of multiple medical experts using a multi-agent Gemini 2.0 system was both exciting and complex. Here’s what we learned along the way:

🧠 Coordinating Multiple AI Agents:
Designing a seamless flow between the Symptom Checker, Prescription Analyzer, and Image Annotator was challenging.Ensuring each agent’s output became another’s input required thoughtful chaining logic and robust memory handling.

📝 Making Sense of Medical Docs:
Extracting structured data from handwritten prescriptions, PDFs, and medical images wasn’t straightforward. OCR issues,layout inconsistencies, and varied formats forced us to iterate on our parsing logic using Gemini Vision APIs and fallbackmodels.

⚡ Latency & Rate Limiting Issues:
Integrating powerful APIs like Gemini 2.0 Flash meant dealing with processing delays and quota limits. We used batching,caching, and a tiered agent-response system to ensure real-time responsiveness.

🎨 Crafting an Intuitive & Reassuring UI:
Balancing clinical precision with a warm, user-friendly interface took several design passes. We aimed for a clean layoutusing Tailwind CSS, shadcn/ui components, and calm color palettes to reduce user anxiety.

🧪 Ensuring Medical Reliability:
Language models can sometimes hallucinate or generalize, so we implemented accuracy flags, disclaimers, and fallbacksuggestions to nudge users toward expert validation when needed.

🗣️ What We’d Love to Build Next ?
💡 While we're proud of what we’ve built, there are several features we couldn’t fit in during this hackathon but would love tobring to life:
📍 Location-Based Pharmacy Suggestions
🔬 Advanced Radiology Assistant
📱 Mobile-First, Always
👩‍⚕️ A Richer Doctor's Portal
🩺 Doctor & Pharmacy Collaboration Portal

Each challenge shaped MediNova into a smarter, more patient-centric product—and our wishlist keeps growing with everynew use case we uncover.