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Vitality AI Health unifies your wearables, blood work, DNA, nutrition, and Epic medical records into one AI longevity dashboard. Track healthspan trends, recovery, and metabolic health. Get personalized insights and predictions, HIPAA-compliant.
There are two ways to build a consumer health AI. The fast way and the responsible way. I want to walk through what the responsible way actually requires.
I'm Duddu Venkata Ramana, Co-Founder and Head of AI & Data Science at Vitality AI Health. Kevin covered the why. Here is the how.
What it is: A production health AI platform with a continuously evaluated safety and quality layer running on top of every response Vaya gives a user.
What makes it different: Most consumer health AI claims safety but cannot prove it. We built the proof.
Across 120+ iterations on Replit, Vaya was graded continuously against four independent evaluation systems totaling 380+ automated checks: a 149-question functional-medicine question bank across 29 categories, an 80-question Dr.-Hyman-caliber clinical bank scored by 6 distinct judge personas (medical professional, health coach, compliance officer, data analyst, patient, investor) against 15 weighted clinical safety rules, a 20-scenario red team adversarial suite, and 164 system-health and data-integrity checks. We did not stop iterating until the 32-question core gate hit 32/32 passing and the red team suite hit 20/20 defended.
Then we layered Arize AX on top, with 5 evaluators and 9 production monitors at 100% sampling, so every live response is scored in real time, not just at test time. The Arize layer covers hallucination, clinical safety, RAG retrieval health, refusal appropriateness, and routing mix drift.
On May 15, we ran the same 32-question stress test against live production Vaya. The result was 0 hallucinations across all 32 questions, 10 appropriate clinical safety redirects on the questions that warranted them, and 16 successful cross-source RAG retrievals. The full audit is available on request.
The stack: Next.js 16 web app, React Native iOS and Android, Supabase backend across all three. Vaya Chat AI runs on Google Gemini with smart routing, around 85% of queries go to gemini-2.5-flash-lite for fast responses and the rest to gemini-3-flash-preview for complex cross-source reasoning. Epic FHIR integration pulls structured medical records directly from your provider, no manual PDF uploads. Wearables come in through the Terra API (60+ wearable brands) plus direct Garmin and Whoop integrations. HIPAA-compliant from day one, designed by Denis Galkin, a virtual CISO with 20+ years of experience supporting organizations in regulated environments and HIPAA Security Rule risk assessments.
Key features under the hood: Real-time clinical safety evaluator with five redlines, including a fifth redline for acute lab and vital interpretation Hallucination zero tolerance monitor on a 15-minute rolling window Refusal appropriateness evaluator so the model is helpful, not just cautious RAG retrieval health scoring on every response Routing mix drift monitor that alerts if model selection patterns shift Daily token cost cap with automated alerting Source attribution on every response, so users see exactly which data table backed each claim Audit logging on every data access and granular per-query consent controls
Benefits: Clinical-grade safety baseline that most consumer health AI products do not have Continuous quality measurement, not a one-shot demo Transparency on every Vaya response, including which data sources it pulled from
Who it's for: Anyone who would not let a consumer chatbot near their actual labs and medical records without proof that the safety layer is real. We built this for that user first.
If you have technical questions about the architecture, the data pipeline, the safety layer, or how we handle Epic FHIR, drop them below. I will answer every one.
— Duddu Venkata Ramana, Ph.D. Co-Founder, Head of AI & Data Science Vitality AI Health
A health dashboard that finally connects every signal you generate. That sounds simple, but the work is in the connecting.
I'm Kevin Amrelle, Founder and CEO of Vitality AI Health.
The problem: Your health data is everywhere, and none of it talks to each other. Your meals are in MyFitnessPal. Your supplements are in SuppCo. Your blood work is in a PDF from Quest. Your DNA report is in your Ancestry account. Your medical history is locked in Epic. Your steps are in Apple Health. Your air quality is on a government EPA dashboard. Your prescriptions are at CVS. Every one of those tells you a piece of the truth. None of them tell you what's actually happening to your body, or what to do about it.
I learned this the hard way. I was in a winter bike race when my heart rate capped at 120 BPM. My cuff confirmed stage 2 hypertension. None of my health apps caught the trend. I built Vitality AI Health so that never happens to anyone again.
What it is: Vitality AI Health is the AI longevity dashboard that unifies every health signal you generate, wearables, blood work, DNA, nutrition, supplements, environmental exposure, and your Epic medical records, into one place. Vaya, our AI coach, finds the correlations no single app can.
What makes it different: Most consumer health apps aggregate one or two data categories. We aggregate every category you actually generate, including the medical-grade ones (Epic FHIR, Labcorp, Quest, 23andMe, AncestryDNA). The product was built HIPAA-compliant from day one, designed by a vCISO with twenty years of healthcare security experience, and the underlying cross-source correlation engine is the subject of a patent application expected to grant in June 2026.
Key features:
30+ data sources unified in one dashboard across wearables, labs, DNA, nutrition, supplements, environmental, and medical records
Vaya Chat AI for natural-language questions across all your data (ask "how did my sleep change after starting Lexapro" and get a grounded answer in 10 seconds)
Healthspan Score across five longevity pillars (cardiovascular, metabolic, sleep and recovery, body composition, resilience)
VAI Score (0-100) measuring how complete your health picture is, so you always know what data to connect next
Trend lines for every biomarker across 7d / 30d / 90d / 1y so you catch problems early
Personalized longevity plan with evidence-based next actions and target ranges
HIPAA-grade audit logging and granular consent controls
Benefits:
Stop logging into eight apps to answer one health question
Catch trend changes early instead of in a clinic six months later
Get longevity-grade insight at $89 per year, not a $20,000 per year protocol price
Who it's for: Longevity-curious people who already track multiple data sources and want them unified. Patients managing chronic conditions who need one view across labs, wearables, and EHR. Health optimizers who want functional-medicine-grade insight at consumer pricing.
Launch offer: $20 off with code VITALITY20 (applies to $89/year annual or $10/month plan). Live on iOS, Google Play, and the web. Install in 60 seconds, connect your devices in 5 minutes. Includes a 30-day money-back guarantee.
Try it at https://vitalityaihealth.com and let us know what data correlation surprises you. We read every comment.
— Kevin Amrelle, Founder and CEO, Vitality AI Health
About Vitality AI Health on Product Hunt
“The car dashboard for your body”
Vitality AI Health was submitted on Product Hunt and earned 5 upvotes and 2 comments, placing #35 on the daily leaderboard. Vitality AI Health unifies your wearables, blood work, DNA, nutrition, and Epic medical records into one AI longevity dashboard. Track healthspan trends, recovery, and metabolic health. Get personalized insights and predictions, HIPAA-compliant.
Vitality AI Health was featured in Health & Fitness (82.7k followers), Artificial Intelligence (469.8k followers) and Alpha (10 followers) on Product Hunt. Together, these topics include over 123.4k products, making this a competitive space to launch in.
Who hunted Vitality AI Health ?
Vitality AI Health was hunted by Rohan Chaubey. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how Vitality AI Health stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Rohan Chaubey
There are two ways to build a consumer health AI. The fast way and the responsible way. I want to walk through what the responsible way actually requires.
I'm Duddu Venkata Ramana, Co-Founder and Head of AI & Data Science at Vitality AI Health. Kevin covered the why. Here is the how.
What it is: A production health AI platform with a continuously evaluated safety and quality layer running on top of every response Vaya gives a user.
What makes it different: Most consumer health AI claims safety but cannot prove it. We built the proof.
Across 120+ iterations on Replit, Vaya was graded continuously against four independent evaluation systems totaling 380+ automated checks: a 149-question functional-medicine question bank across 29 categories, an 80-question Dr.-Hyman-caliber clinical bank scored by 6 distinct judge personas (medical professional, health coach, compliance officer, data analyst, patient, investor) against 15 weighted clinical safety rules, a 20-scenario red team adversarial suite, and 164 system-health and data-integrity checks. We did not stop iterating until the 32-question core gate hit 32/32 passing and the red team suite hit 20/20 defended.
Then we layered Arize AX on top, with 5 evaluators and 9 production monitors at 100% sampling, so every live response is scored in real time, not just at test time. The Arize layer covers hallucination, clinical safety, RAG retrieval health, refusal appropriateness, and routing mix drift.
On May 15, we ran the same 32-question stress test against live production Vaya. The result was 0 hallucinations across all 32 questions, 10 appropriate clinical safety redirects on the questions that warranted them, and 16 successful cross-source RAG retrievals. The full audit is available on request.
The stack: Next.js 16 web app, React Native iOS and Android, Supabase backend across all three. Vaya Chat AI runs on Google Gemini with smart routing, around 85% of queries go to gemini-2.5-flash-lite for fast responses and the rest to gemini-3-flash-preview for complex cross-source reasoning. Epic FHIR integration pulls structured medical records directly from your provider, no manual PDF uploads. Wearables come in through the Terra API (60+ wearable brands) plus direct Garmin and Whoop integrations. HIPAA-compliant from day one, designed by Denis Galkin, a virtual CISO with 20+ years of experience supporting organizations in regulated environments and HIPAA Security Rule risk assessments.
Key features under the hood:
Real-time clinical safety evaluator with five redlines, including a fifth redline for acute lab and vital interpretation
Hallucination zero tolerance monitor on a 15-minute rolling window
Refusal appropriateness evaluator so the model is helpful, not just cautious
RAG retrieval health scoring on every response
Routing mix drift monitor that alerts if model selection patterns shift
Daily token cost cap with automated alerting
Source attribution on every response, so users see exactly which data table backed each claim
Audit logging on every data access and granular per-query consent controls
Benefits:
Clinical-grade safety baseline that most consumer health AI products do not have
Continuous quality measurement, not a one-shot demo
Transparency on every Vaya response, including which data sources it pulled from
Who it's for: Anyone who would not let a consumer chatbot near their actual labs and medical records without proof that the safety layer is real. We built this for that user first.
If you have technical questions about the architecture, the data pipeline, the safety layer, or how we handle Epic FHIR, drop them below. I will answer every one.
— Duddu Venkata Ramana, Ph.D.
Co-Founder, Head of AI & Data Science
Vitality AI Health