[WIP] PRD

Executive Summary

Goal: Launch India's first longevity-focused personal health OS that helps health-conscious Indians own their health data, track biomarkers over time, and optimize for healthspan.

Positioning: Desktop-optimized, family-first longevity data hub (not just another PHR app)

Target Launch: 90 days (Phase 1) + 60 days (Phase 1.5 with longevity features)

Success Criteria (3 months):

  • 500 active users

  • 80%+ OCR accuracy on Indian lab reports

  • 5+ documents uploaded per user

  • 40%+ 30-day retention

  • 100 users tracking biomarker trends monthly

Strategic Context: Based on [[competitors/strategic-insights|competitor analysis]], we have identified:

  • Longevity is the fastest-growing segment ($8.5B global, +220% YoY)

  • Family-first approach is unique (all competitors are individual-focused)

  • Data generation without management is a critical gap (BioPeak, Neko generate 60GB+ data with no storage solution)

  • ABDM integration is table stakes (73+ crore ABHA IDs)

  • Desktop-optimized for family management is differentiated

Related: [[memo]] | [[prd]] | [[product/research/research-summary|research-summary]] | [[competitors/strategic-insights|strategic-insights]]

What Problem Are We Solving?

Primary Problem: Longevity Data Without Management

Health-conscious Indians and longevity enthusiasts generate massive amounts of health data but have nowhere to store and track it long-term:

  • BioPeak longevity clinic clients get 60GB of diagnostic data with no long-term storage

  • Neko Health-style screening generates 50M data points per person - where does it go?

  • Function Health tracks 100+ biomarkers annually - but users can't track year-over-year trends

  • Traditional health checkups create scattered PDFs that can't answer: "Is my cholesterol improving?"

Secondary Problem: Family Health Management

Families need to manage health records for multiple generations:

  • Parents managing aging parents' health remotely

  • Tracking children's vaccinations and growth milestones

  • No single platform for multi-generational health data

  • Market Gap: All competitors focus on individuals, none offer family-first approach

Tertiary Problems

  • Medical records scattered across paper, PDFs, and hospital systems

  • Difficult to share complete health history with new doctors

  • No way to spot concerning trends early (pre-diabetes, hypertension)

  • Cannot understand if lifestyle interventions are working

  • ABDM infrastructure exists (73 crore ABHA IDs) but lacks consumer-friendly interface

Why Now? (Market Timing)

  • Longevity boom: $8.5B global funding (+220% YoY), Bangalore = Top 5 longevity hub

  • BioPeak launch: India's first longevity clinic opened, creating data management need

  • Government infrastructure ready: 73 crore ABHA IDs, ABDM ecosystem live

  • Chronic disease crisis: Diabetes, hypertension prevalence rising

  • Post-COVID health consciousness: Increased focus on preventive health

  • Data generation gap: BioPeak, Neko, Function generate data with no management layer

Insight from [[competitors/strategic-insights]]: Preventive/longevity companies are focused on data generation (testing, screening, biomarkers). No one owns comprehensive data management. AarogyaDost becomes the data layer for India's longevity ecosystem.

MVP Scope - Phased Approach

Phase 1 (Days 0-90): Core Health Vault

A desktop application that enables:

  1. Upload & Digitize: Scan/upload medical documents (PDFs, images)

  2. Smart OCR: Extract biomarker data from Indian lab reports (Thyrocare, Dr. Lal PathLabs, Apollo, SRL)

  3. Organize Records: Timeline view of all health records

  4. Visualize Trends: Line charts showing key biomarkers over time

  5. Secure Storage: Local-first encrypted storage (AES-256)

  6. Family Profiles: Manage health records for up to 5 family members (family-first differentiation)

Phase 1.5 (Days 91-150): Longevity Features

Based on [[product/research/research-summary|research]], add longevity positioning:

  1. Biological Age Calculator: Levine PhenoAge algorithm using 9 blood biomarkers (see [[product/research/biological-age-calculation]])

  2. Peer Comparison Insights: "Your HbA1c is better than 65% of users" using Indian population norms (see [[product/research/peer-insights-garmin-style]])

  3. ABDM Integration (Basic): Fetch health records from ABDM network (table stakes for credibility)

  4. Pollution-Adjusted Insights: AQI impact on health metrics (see [[product/research/environmental-demographic-factors]])

Phase 2 (Months 6-12): Ecosystem & Scale

  • ✅ Mobile apps (iOS/Android) for on-the-go access

  • ✅ BioPeak partnership: Data layer for longevity clinic clients

  • ✅ Multi-language support: Hindi, Tamil, Telugu (India expansion)

  • ✅ Wearable integration: Apple Health, Google Fit, Garmin

  • ✅ Advanced ABDM: Push records to network, consent management

  • ✅ Desktop power features: Spreadsheet view, advanced filtering, bulk operations

What We're NOT Building (Defer to V3+)

  • ❌ AI health recommendations (regulatory complexity)

  • ❌ Doctor collaboration features (marketplace complexity)

  • ❌ Medication reminders (not core differentiation)

  • ❌ Appointment scheduling (service-first, not records-first)

  • ❌ Telemedicine (partnership approach instead)

  • ❌ Genomics data (specialized, expensive)

  • ❌ Social/sharing features (privacy concerns)

  • ❌ Insurance integration (Phase 3 after validation)

User Personas

Primary: "Longevity Optimizer Raj"

Demographics:

  • Age: 32, Male

  • Location: Bangalore (Tier 1 city)

  • Occupation: Software Engineer

  • Income: ₹15-25 LPA

Behaviors:

  • Gets annual health checkups (considering BioPeak comprehensive screening)

  • Tracks fitness via apps (Strava, MyFitnessPal, Garmin)

  • Has 5+ years of lab reports (paper + PDF)

  • Reads longevity content (Bryan Johnson, Peter Attia, Huberman Lab)

  • Interested in biological age and healthspan optimization

Pain Points:

  • Lab reports stored in Gmail, random folders - no longitudinal tracking

  • Can't visualize trends over time ("Is my HbA1c improving?")

  • No way to calculate biological age without expensive tests

  • BioPeak and longevity clinics generate data but provide no storage solution

  • Wants to compare biomarkers to peers but no India-specific data

Goals:

  • Understand health trajectory and optimize for longevity

  • Track biological age vs. chronological age

  • Catch problems early (preventive, not reactive)

  • Be data-driven about health interventions

  • Store and trend data from BioPeak/comprehensive screenings

Success Metric: Uses app weekly to track biomarkers, views biological age monthly, uploads data from all health checkups

Willingness to Pay: ₹499/month for individual longevity tracking

Secondary: "Chronic Condition Manager Priya"

Demographics:

  • Age: 45, Female

  • Location: Mumbai

  • Occupation: Marketing Manager

  • Condition: Pre-diabetic (HbA1c 6.0)

Behaviors:

  • Gets blood tests every 3 months

  • Paper reports in folders at home

  • Concerned about diabetes progression

  • Wants to see if lifestyle changes are working

Pain Points:

  • Difficult to compare HbA1c across quarters

  • Forgets which interventions worked

  • Brings wrong reports to doctor visits

  • Anxious about disease progression

Goals:

  • Track HbA1c trend over time

  • See if diet/exercise is working

  • Avoid progressing to Type 2 diabetes

  • Be prepared for doctor visits

Success Metric: Checks HbA1c trend weekly, uploads new reports within 24 hours

Tertiary: "Family Health Manager Anita" (NEW - Family-First Differentiation)

Demographics:

  • Age: 38, Female

  • Location: Pune (Tier 1 city)

  • Occupation: HR Manager

  • Income: ₹20-30 LPA (household)

Family Context:

  • Managing health for 5 people: Self, husband, 2 kids (ages 6, 10), aging father (age 68)

  • Father has diabetes and hypertension, lives in different city

  • Kids have vaccination schedules, growth tracking needs

  • Husband has high cholesterol

Behaviors:

  • Coordinates doctor visits for entire family

  • Keeps physical folders for each family member's records

  • Shares father's reports with his doctor over WhatsApp

  • Tracks kids' vaccination dates manually in calendar

  • Struggles to remember which family member's test is due when

Pain Points:

  • Managing 5 people's health records across multiple folders/systems

  • Difficult to share father's complete medical history with specialists remotely

  • Forgets vaccination schedules, has to call pediatrician

  • Can't track if father's diabetes is improving quarter-over-quarter

  • No single place for family health history (important for genetic risk assessment)

Goals:

  • Centralized health record management for entire family

  • Easy sharing with doctors (especially for father's remote care)

  • Vaccination reminders and growth tracking for kids

  • Understand family health patterns (diabetes runs in family)

  • Peace of mind that all health data is organized and accessible

Success Metric: Manages health records for all 5 family members, shares father's records with doctor monthly, views family health dashboard weekly

Willingness to Pay: ₹999/month for family plan (up to 5 members)

Why This Persona Matters: [[competitors/strategic-insights]] shows no competitor offers family-first approach. All PHR apps are individual-focused. Family plan is unique differentiation.

Strategic Differentiation

Based on [[competitors/strategic-insights|comprehensive competitor analysis]] of 36 competitors across 10 categories, here are our key differentiation pillars:

1. Longevity-First Positioning (Not Just PHR)

  • Gap Identified: BioPeak, Neko Health, Function Health generate 50-60GB of health data per person with no long-term storage solution

  • Our Approach: Become the data layer for India's longevity ecosystem

  • Market Opportunity: $8.5B global longevity funding (+220% YoY), Bangalore = Top 5 global longevity hub

2. Family-First (Unique Differentiation)

  • Gap Identified: All 36 competitors focus on individuals, none offer family health management

  • Our Approach: Multi-generational health OS - manage self, parents, kids, grandparents in one platform

  • Target: Family plan (₹999/month for up to 5 members) vs. Individual (₹499/month)

3. Desktop-Optimized for Power Users

  • Gap Identified: All competitors are mobile-first; comprehensive family/data management is hard on phones

  • Our Approach: Desktop-first with spreadsheet-like views, bulk operations, multi-profile management

  • User Insight: Managing 5 family members' health records requires desktop power tools

4. Records-First, Not Service-First

  • Gap Identified: Practo, MediBuddy, Apollo 247 prioritize consultations/pharmacy over data management

  • Our Approach: Focus on comprehensive health data management; partner for services (not compete)

  • Partnership Strategy: BioPeak for diagnostics, Emoha for eldercare, 1MG for pharmacy - we manage the data layer

5. India-First with ABDM Integration

  • Gap Identified: Neko, Function Health, Prenuvo focused on US/Europe; India market open

  • Our Approach: ABDM-native integration (73 crore ABHA IDs), India-specific biomarker standards (BHARAT Study), local pricing

  • Competitive Advantage: While global players ignore India, we build India-first longevity platform

6. Privacy & User Ownership

  • Gap Identified: Hospital-led apps (Fortis, Apollo) lock data in their ecosystems

  • Our Approach: User-owned, local-first, export anytime, no selling data to pharma/insurance

  • Trust Builder: Transparent privacy model differentiates from corporate/hospital-owned PHRs

7. Smart OCR for Indian Medical Documents

  • Gap Identified: OCR solutions optimized for Western lab reports; Indian formats (Thyrocare, Dr. Lal PathLabs) are different

  • Our Approach: Train OCR specifically for Indian lab report formats, multi-language support (Hindi, Tamil, Telugu)

8. Complementary Platform (Partnership Moat)

  • Strategic Insight: BioPeak generates 60GB of data per client with no storage solution

  • Partnership Opportunity: Become official data layer for BioPeak clients, longevity clinics, comprehensive screening providers

  • Win-Win: They focus on diagnostics/services, we manage longitudinal data tracking

Market Positioning Matrix

Our Position: Bottom-right quadrant

  • Records-first (unlike service platforms)

  • Longevity-focused (unlike basic PHR)

  • Family-first (unique)

  • Data aggregation hub (captures what longevity clinics generate)

MVP User Stories

Epic 1: Document Upload & Digitization

Story 1.1: Upload PDF Lab Report

Story 1.2: OCR Extract Biomarkers from Lab Report

Story 1.3: Manual Data Entry (Fallback)

Epic 2: Health Record Organization

Story 2.1: View Timeline of All Records

Story 2.2: Search and Filter Records

Story 2.3: View Original Document

Epic 3: Trend Visualization & Insights

Story 3.1: View Biomarker Trend Chart

Story 3.2: Dashboard View (Quick Overview)

Epic 4: Data Security & Privacy

Story 4.1: Local Encrypted Storage

Story 4.2: App Password Protection

Story 4.3: Export Data

Epic 5: Onboarding & Setup

Story 5.1: First-Time User Onboarding

Story 5.2: Sample Data Mode

Technical Requirements

Platform

  • Target OS: macOS (11.0+), Windows 10+

  • Architecture: Desktop-first, local-first

  • Framework Options: Electron, Tauri, or native (Swift/Kotlin)

Performance

  • App Launch: <3 seconds

  • Document Upload: <5 seconds per file

  • OCR Processing: <30 seconds per document

  • Timeline Load: <2 seconds (100+ documents)

  • Chart Render: <1 second

  • Search Results: <500ms

Storage

  • Database: SQLite (local)

  • File Storage: Local filesystem

  • Encryption: AES-256

  • Estimated Size: 50MB-1GB per user

OCR Engine

  • Options: Tesseract (open-source), Google Cloud Vision API, AWS Textract

  • Target Accuracy: 85%+ for standard Indian lab reports

  • Supported Formats: PDF (MVP), JPEG/PNG (V1.5)

  • Supported Labs: Thyrocare, Dr. Lal PathLabs, Apollo, SRL

Data Model

Success Metrics & KPIs

North Star Metric

Monthly Active Users (MAU) tracking at least 1 biomarker trend

Why: Core value is longitudinal health tracking. If users aren't viewing trends, we're not solving the problem.

Adoption Metrics

Metric
Target (Month 1)
Target (Month 3)
How to Measure

Total Users

100

500

Sign-ups (app installs)

Active Users (MAU)

60

300

Opened app at least once in 30 days

Documents Uploaded

300

2,500

Total documents across all users

Docs per User

3

5

Average documents per user

Engagement Metrics

Metric
Target
How to Measure

30-Day Retention

40%

% of users who return after 30 days

90-Day Retention

25%

% of users who return after 90 days

Weekly Active Users

40% of MAU

% who use app weekly

Avg Session Duration

5 min

Time spent per session

Sessions per Month

4

Number of times user opens app per month

Charts Viewed per Session

2

Number of biomarker trends viewed

Search Queries per User

1 per week

Search usage frequency

Product Quality Metrics

Metric
Target
How to Measure

OCR Accuracy

85%

% of correctly extracted values (sample audit)

OCR Success Rate

80%

% of documents successfully processed

Manual Corrections

<20%

% of users who manually edit OCR data

App Crash Rate

<1%

% of sessions with crashes

Load Time (P95)

<3s

95th percentile timeline load time

Bugs Reported per User

<0.5

Average bugs reported per active user

User Satisfaction Metrics

Metric
Target
How to Measure

Net Promoter Score (NPS)

40+

"How likely are you to recommend?" (0-10 scale)

Feature Satisfaction

4.0/5.0

In-app rating per feature

Support Tickets per User

<0.3

Number of support requests per active user

User Reviews (App Store)

4.5+ stars

Average rating when published

Business Metrics (Future)

Metric
Target
Notes

Paid Conversion

TBD

For when pricing is introduced

Customer Acquisition Cost

TBD

Post-launch tracking

Lifetime Value

TBD

Once monetization is live

Instrumentation Requirements

Events to Track

Onboarding Events

Document Upload Events

Engagement Events

Export Events

Error Events

Analytics Tools

Option 1: Self-hosted (Privacy-first)

  • Plausible Analytics (open-source, privacy-focused)

  • PostHog (open-source, self-hosted option)

  • Matomo (open-source)

Option 2: Cloud-based

  • Mixpanel (product analytics)

  • Amplitude (product analytics)

  • PostHog Cloud (easier setup)

Recommendation: PostHog (open-source, good balance of privacy and features)

Privacy Considerations

  • ✅ No PII in events (use anonymous user IDs)

  • ✅ No biomarker values in events (only counts)

  • ✅ No document content in events

  • ✅ User consent required for analytics

  • ✅ Opt-out option in settings

  • ✅ Data minimization (only track what's needed)

Feature Prioritization (MoSCoW)

Must Have (MVP - Ship This First)

  • ✅ Upload PDF documents

  • ✅ OCR extract biomarkers (85%+ accuracy)

  • ✅ Timeline view of documents

  • ✅ Trend charts for 12 core biomarkers

  • ✅ Local encrypted storage

  • ✅ Password protection

  • ✅ Search and filter

  • ✅ Manual data entry (fallback)

Should Have (V1.1 - 30 Days Post-MVP)

  • Image upload (JPEG/PNG)

  • Improved OCR accuracy (90%+)

  • More biomarker support (25 total)

  • Dashboard view

  • Data export (JSON/CSV)

  • Better error handling

  • Onboarding tutorial

Could Have (V1.5 - 60 Days Post-MVP)

  • ABDM integration

  • Cloud backup (encrypted)

  • Biological age calculator

  • Peer comparison insights (population norms)

  • Report generation for doctors

  • Multi-language support (Hindi)

  • Dark mode

Won't Have (Defer to V2+)

  • Mobile apps

  • Family profiles

  • AI recommendations

  • Doctor collaboration

  • Medication tracking

  • Appointment scheduling

  • Wearable integration

  • Social features

Launch Criteria (Definition of Done)

Product Readiness

Content Readiness

Analytics Readiness

Go-to-Market Readiness

MVP Development Timeline

Week 1-2: Foundation

  • Set up development environment

  • Choose tech stack (Electron vs Tauri vs native)

  • Database schema design

  • Authentication & encryption setup

  • Basic UI framework

Week 3-4: Document Upload & Storage

  • File upload UI

  • Local file storage

  • Document listing (timeline view)

  • Search functionality

Week 5-7: OCR & Data Extraction

  • OCR engine integration

  • Biomarker extraction logic

  • Manual correction UI

  • Data validation

Week 8-10: Visualization

  • Trend chart implementation (12 biomarkers)

  • Dashboard view

  • Reference range overlays

  • Time range selectors

Week 11-12: Polish & Testing

  • UI/UX refinement

  • Bug fixes

  • Performance optimization

  • Beta testing with 20 users

  • Analytics integration

Week 13: Launch

  • Package and distribute app

  • Launch landing page

  • Announce to beta list

  • Monitor metrics and feedback

Post-MVP Roadmap Priorities

Month 2: Feedback & Iteration

  • Fix top bugs reported by users

  • Improve OCR accuracy based on real data

  • Add most-requested biomarkers

  • Optimize performance bottlenecks

Month 3: Growth Features

  • ABDM integration (expand to ABDM ecosystem)

  • Cloud backup option

  • Referral program

  • Content marketing push

Month 4-6: Differentiation

  • Biological age calculator

  • Peer comparison insights

  • AI-powered anomaly detection

  • Report generation for doctors

Risk Assessment

Risk
Impact
Likelihood
Mitigation

OCR accuracy too low

High

Medium

Start with structured lab reports; iterate; offer manual entry

User doesn't have old records

High

Medium

Focus on longitudinal value; encourage upload after each checkup

Adoption too slow

High

Medium

Aggressive beta testing; doctor partnerships; content marketing

Privacy concerns

High

Low

Strong encryption; local-first; transparent security messaging

Competition launches faster

Medium

Medium

Focus on differentiation (longevity focus); ship fast

OCR costs too high (cloud API)

Medium

Low

Evaluate open-source alternatives (Tesseract)

App performance issues

Medium

Medium

Load testing; optimize early; target modern hardware

Regulatory issues (medical device)

High

Low

Legal review; position as "record keeping" not "diagnosis"

Open Questions (Decisions Needed)

Technical

  1. Tech stack: Electron, Tauri, or native apps?

  2. OCR approach: Tesseract (free, lower accuracy) vs Cloud API (paid, higher accuracy) vs Hybrid?

  3. Analytics: PostHog vs Mixpanel vs Plausible?

  4. Error tracking: Sentry vs Bugsnag?

Product

  1. Platform priority: macOS first or Windows first or both simultaneously?

  2. Sample data: Include sample dataset for onboarding?

  3. Biomarker priority: Which 12 biomarkers to support in MVP?

  4. Manual entry: How detailed should manual entry form be?

Business

  1. Pricing Strategy (Updated based on [[memo]]):

    • Free MVP for first 3 months to gain early adopters and feedback

    • Freemium Model starting Month 4:

      • Free tier: Basic document storage + timeline view (limited to 10 documents)

      • Individual Premium: ₹499/month - Unlimited documents, biomarker tracking, trend charts

      • Family Plan: ₹999/month - Up to 5 family members, all premium features

    • Phase 1.5 Longevity Tier (Month 5+): ₹499/month individual, ₹999/month family - includes biological age, peer insights, ABDM integration

    • Strategic Pricing: ₹999 is below coaching apps (₹2,000-5,000), above free PHRs, positioned as longevity investment

  2. Beta program: Open beta with waitlist to create demand

  3. Launch channels: Product Hunt, Hacker News, LinkedIn, Health-tech communities, BioPeak partnership

Legal

  1. Medical device classification: Do we need approval from regulatory authority?

  2. DPDP compliance: Full legal review needed before launch?

  3. Terms & Privacy: Need legal counsel or use templates?

Related Documents

  • [[memo]] - Product vision

  • [[prd]] - High-level PRD

  • [[research-summary]] - Research overview

  • [[mvp-metrics-framework]] - Detailed metrics tracking

  • [[mvp-technical-requirements]] - Technical specifications

Next Steps

  1. Decision-making: Resolve open questions (RFC process)

  2. Team assembly: Hire/contract developers

  3. Sprint planning: Break user stories into tasks

  4. Design: Create mockups and prototypes

  5. Development: Start Week 1-2 foundation work

Status: Ready for development ✅

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