Train, track, and stay consistent even offline.
GymAI is an AI-powered fitness and nutrition platform for people who want personalized workout plans, practical diet guidance, and long-term progress tracking in one app. It is designed for users in low-connectivity environments as well as a global audience that needs accessibility, localization, and resilient data sync across devices.
Busy Professional Aisha, 32 - Aisha works long hours, trains before work, and often has unreliable mobile data on her commute. She wants a plan that always works, even when her connection drops in the gym basement.
New Gym User Rahul, 24 - Rahul is new to structured fitness and needs simple guidance, large readable screens, and local-language support. He is easily overwhelmed by complex apps and needs a guided experience.
Coach/Trainer Maya, 40 - Maya manages a small client base and needs reliable client adherence data. She cares about whether users complete workouts and keep logging, even in bad network conditions.
Aisha leaves work, heads to the gym, and opens GymAI on a weak mobile connection. Her workout plan and exercise instructions are already downloaded, so she starts immediately, logs sets and water intake offline, and finishes the session without worrying about signal drops.
Later, when her phone reconnects, GymAI syncs her workout completion and measurements automatically. If another device has a newer edit, the app resolves it predictably and shows what changed, keeping her data trustworthy without interrupting her routine.
Over time, Aisha sees that she never loses progress and can train consistently anywhere. For the business, this means higher retention, fewer support issues, and a product experience that works in real-world connectivity conditions instead of ideal ones.
Team & resourcing - Small cross-functional team - 3 engineers, 1 designer, 1 QA, part-time PM, and part-time localization/accessibility support.
Paste this into Cursor, Bolt, Lovable, or v0 to start building.
Build a Flutter mobile app called GymAI, an AI-powered fitness and nutrition platform with offline-first workout tracking, background synchronization, accessibility, and localization. Primary goals: Allow users to download workout plans and diet plans, start and complete workouts offline, log exercise sets, water intake, body measurements, and weight offline, then sync safely when connectivity returns. Support TalkBack and VoiceOver, WCAG 2.2 AA-friendly UI patterns, and localization for English, Hindi, and Spanish. Core screens and flows: 1. Auth screen with email, Google, and Apple sign-in. 2. Onboarding flow for goal, experience level, schedule, equipment, language, and consent. 3. Home dashboard showing today’s workout, sync status, offline state, and progress summary. 4. Workout detail screen with cached instructions, timer, exercise logging, and completion state. 5. Diet plan screen with offline meal guidance and progress tracking. 6. Metrics screen for weight, measurements, water intake, and trends. 7. Settings screen for language, accessibility options, storage management, privacy policy, terms, export data, and delete account. Data model: User, Profile, Plan, WorkoutSession, ExerciseSet, NutritionLog, WaterLog, MeasurementLog, OfflineQueueItem, SyncState, LegalDocumentVersion, ConsentRecord, NotificationPreference, LocaleSetting. Each offline-created record must have local id, server id if synced, createdAt, updatedAt, syncStatus, and conflict metadata. Offline-first behavior: Use a local database such as Drift or Isar for all user-generated data and cached plans. Queue mutations locally first, then sync via background jobs with retry and exponential backoff. Show pending, syncing, synced, and conflict states clearly. Implement deterministic conflict handling using version numbers and server timestamps. Preserve local data after app restarts and handle low-storage and no-network cases gracefully. Tech stack: Flutter frontend, Dart state management with Riverpod or BLoC, local persistence with Drift or Isar, backend API with Node.js and NestJS, PostgreSQL, Redis queue, object storage for media assets, Sentry for errors, and OpenTelemetry for tracing. Build clean, production-ready UI with accessible components, semantic labels, large touch targets, strong contrast, skeleton loading, and responsive layouts. Include sample seed data, empty states, error states, and mocked sync status transitions for demo purposes.
[11:43 AM, 8/5/2026] Alok: Phase 24 – Offline Mode, Synchronization & Data Resilience 24.1 Objective GymAI ko is tarah design kiya jayega ki users weak internet ya bina internet ke bhi core fitness features use kar saken. Connection wapas aane par data safely synchronize ho aur data loss na ho. --- 24.2 Offline-First Strategy Design Principles: - Local-first data access - Background synchronization - Automatic retry - Conflict resolution - Data integrity - Minimal user interruption --- 24.3 Features Available Offline Users should be able to: - View downloaded workout plans - Start and complete workouts - Log completed exercises - Use workout timer - View saved exercise instructions - Log weight - Log body measurements - Log water intake - View previously downloaded diet plans Features req… [11:43 AM, 8/5/2026] Alok: Phase 25 – Accessibility, Localization & Internationalization (i18n) 25.1 Objective GymAI ko inclusive, accessible aur globally scalable application ke roop mein design kiya jayega. Har user, chahe uski language, device, region ya accessibility needs kuch bhi ho, app ko easily use kar sake. --- 25.2 Accessibility Principles The application should follow: - Inclusive Design - Accessibility by Design - Consistent Navigation - Readable Content - Touch-Friendly Interactions Target standard: - WCAG 2.2 Level AA (where applicable) --- 25.3 Screen Reader Support Support: - Android TalkBack - iOS VoiceOver Requirements: - Semantic labels for buttons - Accessible form fields - Image descriptions where meaningful - Proper heading hierarchy - Accessible dialogs and me… [11:43 AM, 8/5/2026] Alok: Phase 26 – Legal Documentation, Privacy Policy, Terms of Service & Regulatory Compliance 26.1 Objective GymAI ka legal framework users, business aur platform ko transparent, secure aur compliant environment provide karega. Is phase ka objective legal requirements ko define karna hai taaki application production deployment aur app store release ke liye ready ho. --- 26.2 Legal Documentation The application should maintain the following legal documents: - Privacy Policy - Terms of Service - End User License Agreement (EULA) (where applicable) - Cookie Policy (for web components, where applicable) - Refund Policy - Community Guidelines - Copyright Policy All legal documents should be version-controlled and easily accessible within the application. --- 26.3 Pr… [11:44 AM, 8/5/2026] Alok: Phase 27 – Launch Strategy, Marketing, Growth & Go-To-Market (GTM) Plan 27.1 Objective GymAI ka Go-To-Market (GTM) strategy ka objective hai product ko successfully launch karna, initial users acquire karna aur sustainable growth achieve karna. Strategy product quality, community building aur data-driven marketing par based hogi. --- 27.2 Launch Phases Phase 1 – Internal Alpha Audience: - Development Team - QA Team Goals: - Fix critical bugs - Validate AI accuracy - Test infrastructure - Verify payment flow Success Criteria: - No critical defects - Stable backend - Production-ready APIs --- Phase 2 – Closed Beta Audience: - 500–2,000 invited users Goals: - Collect real-world feedback - Measure retention - Validate onboarding - Improve AI recommendations … [11:45 AM, 8/5/2026] Alok: Phase 28 – Future Product Roadmap & Version Planning 28.1 Objective Future Product Roadmap ka objective GymAI ke long-term development ko structured direction dena hai. Is roadmap mein feature prioritization, version planning aur innovation strategy define ki jayegi taaki product continuously improve ho aur user needs ke saath evolve kare. --- 28.2 Product Vision Long-Term Vision: «Build GymAI into the world's most intelligent AI-powered fitness ecosystem that delivers personalized workout, nutrition, coaching and wellness experiences.» Core Principles: - AI First - User First - Data Driven - Privacy Focused - Scalable Architecture - Global Accessibility --- 28.3 Version 1.0 – Initial Public Release Core Features: - User Registration & Login - AI Workout… [11:45 AM, 8/5/2026] Alok: Phase 29 – Technical Appendices & Engineering Reference 29.1 Objective Technical Appendices ka objective developers, AI engineers, QA engineers aur DevOps teams ke liye ek complete engineering reference provide karna hai. Is document mein architecture references, coding standards aur implementation guidelines define hongi. --- 29.2 High-Level System Architecture Core Components: - Flutter Mobile App - Admin Web Portal - API Gateway - Authentication Service - AI Service - Workout Engine - Diet Engine - Notification Service - Analytics Service - Payment Service - Database - Object Storage - Monitoring & Logging All services should communicate through secure APIs. --- 29.3 Suggested Project Structure gymai/ ├── mobile_app/ ├── admin_panel/ ├── backend/ ├── ai… [11:46 AM, 8/5/2026] Alok: Phase 30 – Final Master PRD & Executive Summary GymAI – Enterprise Product Requirements Document (Master Version) --- Executive Summary Product Name GymAI Product Category AI-Powered Fitness & Nutrition Platform Vision Build GymAI into one of the world's leading AI-powered fitness platforms that provides personalized workout plans, budget-friendly nutrition guidance, intelligent coaching and long-term health tracking through a secure, scalable and user-centric experience. --- Problem Statement Many fitness applications provide generic workout plans or calorie tracking, but they often fail to adapt to individual goals, budgets, available equipment and changing progress. GymAI aims to solve these challenges by using AI to generate personalized fit…
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