DEV Community: GoDavaii - Advanced Health AI

Day 27: What GPT-4 Hallucinating 'Amritavati' Taught Me About Building Health AI for India

GoDavaii - Advanced Health AI — Sat, 16 May 2026 14:10:01 +0000

GPT-4 hallucinated 'Amritavati' as a real drug yesterday. Confident. Wrong. Dangerous.

For a health platform, this isn't a funny bug. It's why building health AI for India can't be a translation job.

Day 27 of building GoDavaii. We're deep in our AI-verified Desi Ilaaj feature - bringing home remedies into the AI age, cross-verified for safety. That means grappling with frontier model limitations head-on.

The Language Barrier: Beyond Translation

22+ Indian languages isn't just UI work. It's how health concepts are expressed, how symptoms are described, how remedies are understood. A user typing 'tabiyat theek nahi' in Tamil - colloquial for 'not feeling well' - needs an AI that reads the underlying symptoms without losing context. Our AI Health Chat has to parse these nuances.

The real challenge is the cultural knowledge layer. Desi Ilaaj isn't uniformly documented. An LLM trained on English internet data fills gaps with plausible-sounding fiction when faced with region-specific traditional queries. 'Amritavati' was exactly that - a confident hallucination.

Our approach: a dedicated knowledge graph plus a verification layer beyond generic LLM inference.

Cross-Verification: Allopathy Meets Ayurveda

GoDavaii's core moat is cross-verifying allopathic and Ayurvedic remedies - not just within their systems, but against each other. A common fever remedy in one tradition might interact with a prescription from another. No global competitor does this at scale in local languages.

This is an architectural problem. We use fine-tuned models (Gemini 2.5 Flash for summarization and language tasks) plus a custom knowledge graph built by medical professionals and Ayurvedic experts. When a user asks about Desi Ilaaj, we check our verified database first. Only then do we query general models, with strict guardrails to flag hallucinations or low-confidence outputs. 'Amritavati' was caught by this process.

Building for Safety-First

Our Top 14 Global Finalist spot at Startup Flight Vietnam gave us exposure, but the core feedback always circles back to our unique Indian problem set. The people coming online won't be English-first. They'll have health questions specific to their diet, environment, traditional practices, language. This isn't just accessibility - it's safety. Incorrect health information in a trusted AI interface is dangerous.

GoDavaii is a question-builder for families. An extra check before your next appointment. A way to surface sharper questions for doctors. A catch for what a busy clinic visit might miss - especially the interplay of modern medicine and traditional practices.

What health query do you think an English-only AI would struggle with most in India? Let me know in the comments.

Try GoDavaii at godavaii.com

Day 26: Why I'm Building Health AI for India's 22+ Languages, Not Taking a Job

GoDavaii - Advanced Health AI — Fri, 15 May 2026 06:57:01 +0000

People often ask why I'm pouring everything into GoDavaii instead of taking a comfortable job. It's a fair question, especially on Day 26 of a very public sprint. My answer, honestly, often surprises them: because no one else is truly building health AI for the India I know, the one where critical health information is lost in translation, or worse, completely absent from English-first platforms.

The Health Gap English AI Cannot Bridge

Look, global health AI solutions like Epocrates or Medscape are incredible resources, but they're inherently English-centric. That's fine for a large segment of users, but it completely misses the next billion people coming online in India, many of whom are more comfortable thinking and expressing their health concerns in their mother tongue. Imagine an elderly relative in a small town trying to explain their symptoms to a chatbot built on English medical data - the nuances are lost, the context is missing.

This isn't just about translation; it's about deep cultural and linguistic understanding. Our AI Health Chat in 22+ Indian languages isn't a simple Google Translate overlay. It's built to understand local idioms, the specific ways discomfort is described, and the context of life in India. When someone describes feeling unwell in their mother tongue, the AI needs to parse not just the words but the cultural weight behind them. This level of linguistic empathy is critical when dealing with health, where clarity can literally be life-changing.

The Complexity of AI-Verified Desi Ilaaj

One of our most challenging, yet deeply rewarding, features is AI-verified Desi Ilaaj. This isn't just a list of home remedies. It's an intelligent system that cross-references traditional Ayurvedic practices with allopathic medical understanding. Why? Because many families, especially in India, use a mix of both. The challenge isn't just knowing what traditional remedies exist, but understanding their potential interactions with modern medicines.

Consider the rising concerns around medication non-adherence, particularly for chronic conditions. Patients might stop statins or blood pressure medication not because they don't want to get better, but because they're taking a traditional concoction they believe will do the same, or simply because they don't understand the long-term implications in their own language. Our Desi Ilaaj feature aims to surface these potential conflicts and provide clear, AI-verified guidance, helping families make informed decisions without replacing their doctor.

Building this requires robust NLP for each language, a deep and continuously updated medical knowledge graph, and a sophisticated reasoning engine. We're using frontier models like Gemini 2.5 Flash for their impressive context windows and multilingual capabilities, but fine-tuning these for the specific, often low-resource, medical lexicon of Indian languages is a non-trivial task that requires an 'India-first' mindset.

The Sprint, The Vision, and The Unasked Questions

Being a Top 14 Global Finalist at Startup Flight Vietnam 2025 was fantastic validation. The judges were impressed by the scale of the language challenge and the audacity of tackling it. What many didn't explicitly ask was about the sheer volume of cultural and medical data we're synthesizing, particularly for a product that has no signup wall on its core features, making it instantly accessible.

We're building this in public, and Day 26 feels like a sprint and a marathon at the same time. The goal isn't just to build another health app; it's to build one that truly serves the unique needs of India, and by extension, the world's diverse populations. It's about ensuring that health literacy isn't a privilege reserved for English speakers.

What critical health questions do you think are currently being missed because the technology doesn't speak the right language? Drop your thoughts in the comments.

Try GoDavaii in your language at godavaii.com

healthtech #aiinhealthcare #multilingual #indianstartups #buildingpublic #healthai

Day 24: When Medical Nomenclatures Shift, How Does Your Multilingual AI Adapt?

GoDavaii - Advanced Health AI — Wed, 13 May 2026 16:13:44 +0000

We tested Hindi medical reasoning on Claude 4. Here is what broke: a common symptom, described slightly differently across regions, leading to completely divergent advice. Not a hallucination of a drug, but a linguistic drift that impacts health outcomes. This is what we're solving at GoDavaii, and it's a far more complex problem than simply translating medical terms.

Yesterday, headlines across the US and India discussed the renaming of PCOS to Polyendocrine Metabolic Ovarian Syndrome. This isn't just a trivial semantic update; it's a re-evaluation of a condition impacting millions, signaling new diagnostic pathways and treatment understandings. For English speakers, this means updated search queries and new educational materials. But what about the next billion users coming online, seeking health answers in their mother tongue?

The Lingual Labyrinth of Medical Information

Imagine a woman in rural Maharashtra looking up 'PCOS' - or, more likely, its Marathi equivalent. For years, she's understood it a certain way, perhaps through a specific local idiom. Now, with a new scientific understanding, her queries need to evolve, and the AI serving her needs to evolve faster. The challenge isn't merely translating 'Polyendocrine Metabolic Ovarian Syndrome' into 22+ Indian languages accurately. It's about ensuring the underlying medical reasoning, the contextual nuances, and the associated advice are correct and culturally appropriate. This is where generic, English-first LLMs often fall short. They might offer a direct translation, but miss the subtle shifts in understanding required in the vernacular.

Our journey at GoDavaii started with this core insight: health AI cannot truly serve India without deeply understanding its linguistic and cultural diversity. Epocrates and Drugs.com, while excellent, are English-only. Their vast databases don't factor in a farmer in Punjab asking about sardi-zukham (cold and cough) or an aunty in Indore trying to understand drug interactions for her Desi Ilaaj (AI-verified home remedies) alongside allopathic medicines. That cross-verification, in the language you think in, is our real moat.

Building Beyond Translation: GoDavaii's Semantic Layer

When we began building our AI Health Chat, the goal was never just translation. It was about creating a semantic layer that understands local idioms, regional variations in symptom descriptions (like our Tamil AI parsing 'konjam nalla illa' not just as 'not feeling well' but as a specific type of malaise in context), and even the vast lexicon of traditional remedies. This is why our Drug Interaction Checker isn't just a database lookup; it's a dynamic graph that needs to cross-reference allopathic drug data with known traditional medicine interactions, verified by our AI for safety.

This isn't just about language models; it's about knowledge graphs, robust data pipelines, and a continuous feedback loop from our early community. We spend significant time on data curation - not just large datasets of medical texts, but also localized content, verified by experts in respective languages, to ensure accuracy and relevance. The shift in PCOS nomenclature, for instance, triggers an immediate cascade across our knowledge base in every supported language, ensuring that any user querying for related symptoms or conditions receives updated, accurate information.

The Founder's Lens: Shipping and Learning

As a founder, navigating this complexity means constant iteration. We recently placed Top 14 Global at Startup Flight Vietnam 2025, and while the judges loved the vision, the deepest conversations were always about our language stack. How do you scale this? How do you maintain accuracy when language itself is a moving target? These are the questions that keep me up at night.

We're not building a doctor replacement; we're building a preparation tool for families, helping them surface sharper questions for their medical providers. A pregnant woman checking medicine safety in her mother tongue, or a son quickly understanding his father's lab reports in Telugu - these are the moments we're optimizing for. It's about augmenting the family's ability to engage with their health proactively, in a way that truly resonates with them.

The path to serving the next billion isn't paved with simple English-to-Hindi translation APIs; it's built with deep, context-aware, culturally intelligent AI. Try GoDavaii at godavaii.com.

Day 23 Building GoDavaii: Why Language Barriers Aren't Just Translation Problems in Health AI

GoDavaii - Advanced Health AI — Tue, 12 May 2026 16:38:42 +0000

GPT-4's Hindi output is barely functional for nuanced medical queries. Ask any native speaker. That's a problem, especially when a child's medicine dosage depends on cultural context, not just direct translation. I'm Pururva Agarwal, founder of GoDavaii, and on Day 23 of our public sprint, I'm thinking about the hidden complexities that make health AI for India fundamentally different.

My cousin's newborn had a persistent cough. The local pharmacy provided a cough syrup. What wasn't immediately obvious, and wasn't flagged, was that it was an adult formulation. This wasn't a malicious error, but a system gap - a lack of a universal 'second pair of eyes' that could account for age, context, and language.

It's this blend of individual context and systemic oversight that drives GoDavaii. We're building India's Advanced Health AI, not just a chatbot, but a comprehensive platform with an AI Health Chat in 22+ Indian languages, a robust Drug Interaction Checker, AI-verified Desi Ilaaj, and more. And the core technical challenge isn't just about parsing medical terms; it's about understanding health in a way that respects diverse linguistic and cultural realities.

The "Next Billion" Speaks a Different AI Language

When we talk about the 'next billion' coming online, we're not just talking about more users. We're talking about users who primarily communicate in their mother tongue. English-first AI models, even the frontier ones, often stumble here. Their training data skews heavily towards English, leading to:

Semantic Drift: A phrase like "ang dukhte" in Tamil isn't just "not feeling well"; it carries nuances of vague discomfort that a generic sentiment analysis might miss. Our AI Health Chat needs to interpret these specific, often colloquial, symptom descriptions accurately. This requires dedicated language models and extensive, context-rich datasets in each of our 22+ languages.
Medical Terminology Discrepancies: A single ailment can have multiple names across different Indian languages, not to mention the blend of English, Hindi, and local terms within a single sentence (Hinglish, Tanglish, etc.). Our architecture uses a multi-layered NLP approach, combining transformer models fine-tuned on medical texts from India, alongside a carefully curated medical ontology that maps these variations.
Voice-First UX Challenges: Many of our users will interact through voice. Building robust voice-to-text for medical queries in diverse Indian accents and dialects is a monumental task. We're experimenting with open-source speech-to-text models like Whisper, but with heavy post-processing and domain-specific language model adaptation to ensure medical accuracy. This is where a lot of our current research and development effort is focused.

AI-Verified Desi Ilaaj: Bridging Centuries of Knowledge

This is perhaps our most unique and technically challenging moat. Integrating traditional Indian home remedies (Desi Ilaaj) and Ayurvedic practices with modern allopathic medicine isn't just about translation; it's about cross-verification. How do you, as an AI, reconcile the concept of 'cooling' herbs with pharmaceutical drug interactions?

Our approach involves building a sophisticated knowledge graph that links:

Ayurvedic/Traditional Ingredients: Their known properties, potential side effects, and traditional uses.
Allopathic Medicines: Active compounds, mechanisms of action, and established drug interactions.
Scientific Literature: Studies (where available) on traditional remedies, and their chemical interactions.

The 'AI-verification' isn't about validating efficacy (that's for clinical trials) but flagging potential conflicts. Does this Ayurvedic remedy increase the sedative effect of an allopathic drug? Could it interfere with absorption? This demands a reasoning engine capable of complex inference across disparate data sources - a data science nightmare, but a critical need for holistic family health in India.

Building in Public, Day 23: The Long Game

We're Day 23 of a 30-day sprint, publicly tracking our progress. Our current user count is 0, as we're focusing intensely on refining the core architecture and ensuring safety and accuracy before a wider launch. This honesty might seem counterintuitive to some, but to this Dev.to community, I know you appreciate transparency.

Placing as a Top 14 Global Finalist at Startup Flight Vietnam 2025 gave us valuable external validation for the vision, but the real work is in the trenches, wrestling with data quality, model biases, and the sheer complexity of language at scale.

We're not just building a product; we're trying to build a new standard for accessible, context-aware health AI. It's a preparation tool for families, designed to help them ask more precise questions of their doctors and navigate their health journey with more information.

Try GoDavaii at godavaii.com - curious what this community thinks about the unique challenges of building AI for truly multilingual, multi-system health contexts.

The Aunty Test - what Malayalam-speaking patients see when they ask Health AI in their own language

GoDavaii - Advanced Health AI — Tue, 12 May 2026 08:49:20 +0000

Voice query in Malayalam: "thudayil chorachorappu, pus varunnu, enthu cheyyanam?"

Most Health AI built in the last three years is English-first. The translation layer breaks the moment a user types a real query in a language a billion people actually think in.

What a generic Health AI says

You mention itching and pus on thigh. This may be infection. Please consult a doctor. Could you rephrase in English for specific recommendations?

What native multilingual reasoning looks like

Pus varunnathum chorachorappum bacterial infection (likely staph) aakaam. Mupiroin ointment 2% divasam moonnu thavana pukoo. 3 divasathinakam kurayunnillenkil oral antibiotic (Cefadroxil) doctor-um koodi nirdesikkanam.

Why this is the wedge

1.4 billion people don't think in English. Every Health AI built so far has either been English-first (translate-button bolted on) or has had a thin localised veneer over an English model. Neither holds up under a real medical query.

GoDavaii reasons natively in 22 Indian languages including Malayalam, Tamil, Bhojpuri, Marathi, Bengali, Telugu, Kannada, Punjabi, Malayalam, Gujarati, Odia, Urdu and more.

Free on the Play Store: https://play.google.com/store/apps/details?id=com.godavaii.app

Building publicly. Try a query in your home language and tell us where it breaks.

The Aunty Test - what Punjabi-speaking patients see when they ask Health AI in their own language

GoDavaii - Advanced Health AI — Mon, 11 May 2026 10:39:59 +0000

Voice query in Punjabi: "shugar de naal blood pressure di dawai khaani safe hai?"

Most Health AI built in the last three years is English-first. The translation layer breaks the moment a user types a real query in a language a billion people actually think in.

What a generic Health AI says

You seem to be asking about combining diabetes and blood pressure medication. Many combinations are safe but interactions exist. Please rephrase in English for accurate analysis.

What native multilingual reasoning looks like

Metformin te Telmisartan / Amlodipine ekathe khaane safe han - actually diabetic patients vaaste ACE inhibitor (Telmisartan) kidney da bachaa karda hai. Beta blockers (Atenolol) avoid karo agar sugar low ho jaandi hai.

Why this is the wedge

GoDavaii reasons natively in 22 Indian languages including Punjabi, Tamil, Bhojpuri, Marathi, Bengali, Telugu, Kannada, Punjabi, Malayalam, Gujarati, Odia, Urdu and more.

Free on the Play Store: https://play.google.com/store/apps/details?id=com.godavaii.app

Building publicly. Try a query in your home language and tell us where it breaks.

Day 22: My Aunt's Thyroid Tea and the 40% Absorption Gap - Why Health AI Needs Cultural Nuance

GoDavaii - Advanced Health AI — Mon, 11 May 2026 07:41:07 +0000

3.2 seconds. That's how long it took GoDavaii's Drug Interaction Checker to flag a problem thousands of Indian families live with daily. Thyroxin (levothyroxine) taken with morning chai - a ritual in most homes - loses up to 40% absorption. Compounds in tea block the thyroid medication. This isn't rare. It's known. But rushed doctor visits and English-only health AIs miss it because they don't understand chai as a daily anchor.

The Unspoken Interactions: Beyond Pure Chemistry

Most drug interaction checkers focus on chemical compound interactions - drug-drug, drug-food (the obvious ones). But health in India isn't just molecules. It's habits, local remedies, dietary patterns woven into daily life. How many health platforms, globally or locally, genuinely account for a chai habit impacting medication efficacy?

This isn't just about a single medicine. It's about every medicine your family takes. For the next billion people coming online, asking health questions in their mother tongue, these nuances are critical. An AI that can't understand 'konjam nalla illa' in Tamil as a specific symptom description, or cross-reference the components of 'haldi-doodh' with an allopathic prescription, isn't truly serving their needs.

Building for the Next Billion: Language and Desi Ilaaj

This cultural gap is precisely why we're building GoDavaii. Our AI Health Chat in 22+ Indian languages isn't a nice-to-have; it's fundamental. We're not just translating; we're building knowledge graphs that understand the intent and context behind a query in Marathi, Bengali, or Telugu.

This also extends to Desi Ilaaj - AI-verified home remedies. Many traditional tips, like turmeric milk for a sore throat, are now being backed by science. Our challenge is to cross-verify these remedies against modern medicine, ensuring safety and efficacy, instead of simply dismissing them. It's a complex task to map traditional wisdom to active compounds and potential allopathic interactions, but it's a critical layer of trust we're building.

Our journey, validated by being named a Top 14 Global Finalist at Startup Flight Vietnam 2025, has constantly pushed us to think beyond the English-centric health AI paradigm. The questions we're solving aren't about brute-forcing data; they're about building intelligence that understands a diverse, culturally rich patient context.

A Thinking Assistant for Families

GoDavaii is designed as a preparation tool for families. It's a quick double-check on your prescriptions, helping you surface sharper questions for your doctor. It catches what a busy clinic visit might miss. Because ultimately, good health outcomes come from informed conversations with medical professionals, backed by accessible, culturally intelligent data.

As Pururva Agarwal, 27-year-old founder of GoDavaii, I'm transparently building this product, day by day. We're on Day 22 of 30 in our public sprint, aiming to reach 100,000 families across India and the world.

What medicine combination are you, or a family member, taking that you've always wondered about? Drop it in the comments below, and I'll share how GoDavaii would check it.

The Aunty Test - what Kannada-speaking patients see when they ask Health AI in their own language

GoDavaii - Advanced Health AI — Sun, 10 May 2026 05:28:30 +0000

Voice query in Kannada: "magu ge raatri jwara baruttide, oushadhi kodabeka?"

Most Health AI built in the last three years is English-first. The translation layer breaks the moment a user types a real query in a language a billion people actually think in.

What a generic Health AI says

It seems your child has nighttime fever. Please consult a pediatrician. For more specific guidance, kindly rephrase your concern in English.

What native multilingual reasoning looks like

Magu ge raatri jwara 100.4F daati iddare paracetamol syrup (15mg/kg, 6 ganteg ondu sala) kodbahudu. 3 dina meeri mundhuvariddare CBC + urine test maadisi - UTI ya viral fever differentiate aagutte. Sakkat hydration mukhya.

Why this is the wedge

GoDavaii reasons natively in 22 Indian languages including Kannada, Tamil, Bhojpuri, Marathi, Bengali, Telugu, Kannada, Punjabi, Malayalam, Gujarati, Odia, Urdu and more.

Free on the Play Store: https://play.google.com/store/apps/details?id=com.godavaii.app

Building publicly. Try a query in your home language and tell us where it breaks.

The Aunty Test - what Telugu-speaking patients see when they ask Health AI in their own language

GoDavaii - Advanced Health AI — Sat, 09 May 2026 05:08:57 +0000

Voice query in Telugu: "pregnancy lo paracetamol theesukovacha?"

Most Health AI built in the last three years is English-first. The translation layer breaks the moment a user types a real query in a language a billion people actually think in.

What a generic Health AI says

You appear to be asking about paracetamol in pregnancy. Paracetamol is generally considered safe but please consult your obstetrician. Rephrase in English for more details.

What native multilingual reasoning looks like

Pregnancy lo paracetamol (500mg) generally safe - aithe daily 2g kanna takkuva. First trimester lo NSAIDs (ibuprofen, diclofenac) avoid cheyandi. Fever 100.4F daatithe 24 ganta-lo OB-GYN ni kalavandi.

Why this is the wedge

GoDavaii reasons natively in 22 Indian languages including Telugu, Tamil, Bhojpuri, Marathi, Bengali, Telugu, Kannada, Punjabi, Malayalam, Gujarati, Odia, Urdu and more.

Free on the Play Store: https://play.google.com/store/apps/details?id=com.godavaii.app

Building publicly. Try a query in your home language and tell us where it breaks.

Day 19 of GoDavaii: The 3-Month Deep Dive into Drug Interactions Medical School Skips

GoDavaii - Advanced Health AI — Fri, 08 May 2026 05:57:38 +0000

Medical schools give you one week on drug interactions. I've spent three months just modeling the architecture for GoDavaii's interaction checker - and I'm still finding edge cases that would terrify a pharmacologist.

This isn't about memorizing a list. It's about understanding the dynamic interplay of chemistry, physiology, and language in a way no static database can capture. Building an advanced health AI for families in India means grappling with medical diversity and linguistic nuance that most global platforms simply ignore.

Beyond the Lookup Table: Building a Dynamic Interaction Graph

When we talk about 'drug interactions,' many people picture a simple spreadsheet lookup: Drug A + Drug B = Warning. If only it were that straightforward. In India, where polypharmacy is common, and prescriptions often include multiple active ingredients in a single medicine, the problem quickly escalates into a multi-dimensional graph.

Our approach for GoDavaii's interaction checker moves beyond simple boolean flags. We're modeling chemical pathways, metabolic enzymes, and physiological effects across thousands of medicines. This means understanding not just 'does X interact with Y?' but 'how does X, in combination with Y and Z, affect this specific pathway in a body also taking a traditional remedy for a cough?' The graph architecture allows us to identify subtle, sometimes dangerous, interactions that a flat database would miss.

For a developer audience, think of the complexity of managing dependencies in a large software project, but with human lives at stake. We're not just running regex on ingredient lists; this is a true graph problem involving pharmacokinetics and pharmacodynamics, requiring constant data ingestion and intelligent contextualization.

The Language Barrier isn't Just Translation: Contextual AI for India

One of GoDavaii's strongest moats, and certainly one of its biggest technical challenges, is our support for 22+ Indian languages. Most 'AI health' platforms are built on English-first models, and their attempts at localization often fall flat. It's not enough to simply translate 'fever' into 'bukhaar' or 'jvar'.

Consider an elderly aunty in Indore asking our AI Health Chat, "mujhe thoda theek nahi lag raha hai, aur ghutno mein dard hai" (I'm not feeling well, and my knees hurt). An English-trained model might struggle to parse the nuance of "thoda theek nahi lag raha hai" - it's not a precise medical term, but a common colloquialism for general malaise. Our AI needs to understand this context, relate it to potential symptoms, and then cross-reference it with any medicines or Desi Ilaaj (home remedies) she might be considering.

This isn't just about translating drug names; it's about understanding culturally specific symptom descriptions, regional dialects, and the natural flow of conversation in various mother tongues. We're building for users coming online who will primarily interact with technology in their native language, and whose health questions are often lost in translation by English-only AI.

AI-Verified Desi Ilaaj: Bridging Allopathy and Tradition Safely

Another genuinely unique aspect of GoDavaii is our AI-verified Desi Ilaaj feature. In India, traditional home remedies - drawing from Ayurveda, Unani, Siddha, and folk medicine - are deeply ingrained in family healthcare. But how do these interact with modern allopathic medicines? The answer is often unknown, leading to potential risks.

Our system tackles this by using AI to cross-reference known components and effects of traditional remedies with allopathic drugs. It's not about validating or disproving Desi Ilaaj, but about identifying potential contraindications or dangerous interactions. This gives families a more complete safety picture, bridging two often separate worlds of medical knowledge, and offering a level of integrated health insight no global competitor even attempts.

GoDavaii: A Thinking Assistant for Families, Not a Medical Provider

Let me be absolutely clear: GoDavaii is an information layer between you and the doctor. Indian doctors, especially in busy clinics, often see 40-60 patients a day. They physically cannot spend an hour checking every single potential interaction for someone on multiple medicines, or fully explaining complex lab reports in multiple languages.

GoDavaii is designed to augment the doctor's role, not replace them. We empower families to raise the questions that matter, catch what a 7-minute appointment might have missed, and understand their health information more deeply. Being named a Top 14 Global Finalist at Startup Flight Vietnam 2025 was a validation of this unique, context-aware approach to health AI.

What are the overlooked health challenges you believe AI should tackle, especially in diverse cultural contexts like India? Drop your thoughts below, or explore the GoDavaii platform and its features at godavaii.com.

healthtech #ai #india #buildinpublic #startup #machinelearning

The Aunty Test - what Bengali-speaking patients see when they ask Health AI in their own language

GoDavaii - Advanced Health AI — Fri, 08 May 2026 05:51:53 +0000

Voice query in Bengali: "matha betha ar bomi bomi bhab, ki khabo?"

Most Health AI built in the last three years is English-first. The translation layer breaks the moment a user types a real query in a language a billion people actually think in.

What a generic Health AI says

You mentioned headache and nausea sensation. Common causes include migraine. Please consult a doctor and consider rephrasing in English for clearer medical advice.

What native multilingual reasoning looks like

Matha betha + bomi bomi bhab migraine er classic combination. Andhar ghor, thanda paani-r compress, ar Domperidone (10mg) + Naproxen (250mg) khaowa jete pare. 3 din-er beshi thakle MRI kora uchit.

Why this is the wedge

GoDavaii reasons natively in 22 Indian languages including Bengali, Tamil, Bhojpuri, Marathi, Bengali, Telugu, Kannada, Punjabi, Malayalam, Gujarati, Odia, Urdu and more.

Free on the Play Store: https://play.google.com/store/apps/details?id=com.godavaii.app

Building publicly. Try a query in your home language and tell us where it breaks.

The Aunty Test - what Marathi-speaking patients see when they ask Health AI in their own language

GoDavaii - Advanced Health AI — Thu, 07 May 2026 05:05:22 +0000

Voice query in Marathi: "sugar chi gholi ghetli tari BP high yetoy, kay karu?"

Most Health AI built in the last three years is English-first. The translation layer breaks the moment a user types a real query in a language a billion people actually think in.

What a generic Health AI says

It looks like your BP is high despite diabetes medication. Diabetes and hypertension are different conditions. Please rephrase in English so I can provide accurate guidance.

What native multilingual reasoning looks like

Diabetes chi golya BP la control karat nahit - donhi vegli aushad lagtat. Tumcha BP reading kay aahe? 140/90 paeksha jaast astil tar Telmisartan ki Amlodipine baddal doctor-shi boluya. Diabetic asal tar ACE inhibitor preferred.

Why this is the wedge

GoDavaii reasons natively in 22 Indian languages including Marathi, Tamil, Bhojpuri, Marathi, Bengali, Telugu, Kannada, Punjabi, Malayalam, Gujarati, Odia, Urdu and more.

Free on the Play Store: https://play.google.com/store/apps/details?id=com.godavaii.app

Building publicly. Try a query in your home language and tell us where it breaks.