Every morning, my grandmother takes four different medicines. For years, I watched her, and honestly, it bothered me that not once had any doctor, or even our family, consistently checked if those medicines interacted. Not just with each other, but with her diet, or the occasional home remedy. That gap became the burning reason I started GoDavaii.
I'm Pururva Agarwal, 27, and I'm not a doctor. I'm a founder from India, building GoDavaii - India's Advanced Health AI. Day 9 of 30. We're targeting 100,000 families across India and the world who deserve better health insights. My family speaks Hindi and Marathi, and I've seen firsthand how language and cultural nuances can create critical blind spots in healthcare.
The Unseen Challenge: 22+ Indian Languages
When we talk about AI health chat, most solutions default to English. But in India, that's just not enough. Imagine trying to explain a complex symptom or understand a medicine's side effect in a language that isn't your primary one, especially for older family members. The nuance is lost, the worry amplified. This is why GoDavaii's AI Health Chat works in over 22 Indian languages. It's not just about simple translation; it's about cultural context, local idioms, and understanding what matters in regional health conversations.
Building this means dealing with diverse datasets, training large language models like Gemini 2.5 Flash on specific linguistic and medical corpora, and ensuring accuracy across different scripts and regional variations. It's a massive undertaking, far more complex than a standard NLP task, because a misinterpreted medical query can have serious consequences. Our interaction checker, for instance, has to understand compound queries across languages, where a user might mix terms or describe traditional remedies alongside allopathic medicines.
Integrating Desi Ilaaj: AI-Verified Home Remedies
Here's where things get really unique globally: AI-verified Desi Ilaaj. Many Indian families rely on home remedies - Ayurvedic practices, traditional concoctions passed down generations. The challenge? Scientific validation is often missing, and more critically, interactions with modern allopathic medicines are rarely, if ever, considered. No global competitor even attempts this integration.
Our system cross-verifies these traditional remedies against modern pharmaceutical data. This isn't about validating or dismissing traditional medicine; it's about providing an AI-powered second pair of eyes that can flag potential conflicts. If a user inputs a common Ayurvedic ingredient, our platform can explain known interactions with prescribed drugs. This helps families raise the questions that matter to their doctors, bridging a massive gap in holistic care that's unique to the Indian family reality - multi-generational homes, language barriers, specific dietary practices like fasting, or considerations during pregnancy.
Building in Public: Lessons from Day 9
Building GoDavaii is a deeply personal journey. I'm building in public because transparency is vital, especially in health-tech. It's not just about the code or the AI models; it's about the trust we earn, one family at a time. Day 9 reminds me that while the technical challenges are immense, the human need is even greater. Every line of code, every data point, is informed by that initial worry I felt for my grandmother.
We're pushing hard, iterating daily, and focusing on making the core features like our Drug Interaction Checker and Pregnancy medicine safety checker as intuitive and helpful as possible. This isn't about replacing your doctor; it's about empowering families with a thinking tool, a pre-doctor checklist that helps surface questions a hurried check-up might miss. It's about giving them information in their language, relevant to their lives.
What are the specific health-tech challenges you believe are most overlooked when building for diverse populations? Drop your thoughts and questions in the comments below. I'm always keen to learn from other builders and users.
Top comments (0)