FitAI Smart Trainer - Sell Project

Project Overview

FitAI Smart Trainer is an AI-powered fitness trainer that counts push-ups in real-time using a webcam. No wearable devices or sensors are needed — the system uses pose detection to understand body position, count reps automatically, and display form feedback.👟 Features• Real-time push-up counter• Works directly in browser (Streamlit)• Accurate AI pose-tracking (OpenCV + Mediapipe)• Clean & easy-to-read Python code• Works on laptop / desktop webcam• Can be rebranded & resold📦 What You G...

Detailed Description

FitAI Smart Trainer is an AI-powered fitness trainer that counts push-ups in real-time using a webcam. No wearable devices or sensors are needed — the system uses pose detection to understand body position, count reps automatically, and display form feedback.


👟 Features

• Real-time push-up counter

• Works directly in browser (Streamlit)

• Accurate AI pose-tracking (OpenCV + Mediapipe)

• Clean & easy-to-read Python code

• Works on laptop / desktop webcam

• Can be rebranded & resold


📦 What You Get

• Full Source Code

• Setup & Installation Guide

• UI + Logic Explanation

• 7 Days Technical Support

• Commercial Rebranding Rights


💼 Ideal For

• Fitness trainers moving to online coaching

• Startup founders exploring AI Fitness platforms

• Agencies who resell software solutions

• Gym owners looking to offer digital plans


💰 Price

$79 one-time (negotiable for agency licensing)


If you'd like a demo — just ask! :)


Content Freshness & Updates

Project Timeline

Created: November 5, 2025 at 4:23 AM (1 month ago)

Last Updated: December 6, 2025 at 1:12 AM (1 day ago)

Update Status: Updated 1.4997161251968 days ago - Recent updates

Version Information

Current Version: 1.0 (Initial Release)

Development Phase: Production Ready - Market validated and ready for acquisition

Next Update: <p>Add new features and improvements to increase user engagement</p><p>Run targeted marketing on social media to attract users</p><p>Offer premium / subscription-based features to monetize</p><p>Integrate additional automation or AI-based enhancements</p><p>Continuously update UI/UX and release new versions to keep users active</p>

Activity Indicators

Project Views: 15 total views - Active engagement

Content Status: Published and publicly available

Content Freshness Summary

This project information was last updated on December 6, 2025 and represents the current state of the project. The content is very fresh and reflects recent developments.

Visual Content & Media

Project Screenshots & Interface

The following screenshots showcase the visual design and user interface of FitAI Smart Trainer:

Screenshot 1: Main Dashboard & Primary Interface

This screenshot displays the main dashboard and primary user interface of the application, showing the overall layout, navigation elements, and core functionality. The interface demonstrates the modern design principles and user experience patterns implemented using • Python (Core Logic),OpenCV (Real-time body movement tracking),MediaPipe Pose (Push-up angle + rep detection),• NumPy & Pandas (Workout stats logging),• Streamlit (Frontend web interface),Firebase / Google Sheets (Workout history storage - optional).

Visual Content Summary

This project includes 1 screenshotno videos, providing comprehensive visual documentation of the saas application. The media content demonstrates the project's technical implementation using • Python (Core Logic),OpenCV (Real-time body movement tracking),MediaPipe Pose (Push-up angle + rep detection),• NumPy & Pandas (Workout stats logging),• Streamlit (Frontend web interface),Firebase / Google Sheets (Workout history storage - optional) and user interface design, showcasing both the visual appeal and functional capabilities of the solution.

Technical Specifications & Architecture

Technology Stack & Implementation

Primary Technologies: • Python (Core Logic),OpenCV (Real-time body movement tracking),MediaPipe Pose (Push-up angle + rep detection),• NumPy & Pandas (Workout stats logging),• Streamlit (Frontend web interface),Firebase / Google Sheets (Workout history storage - optional)

Technology Count: 6 different technologies integrated

Implementation Complexity: High - Multi-technology stack requiring extensive integration expertise

Technology Analysis

• Python (Core Logic): High-level programming language known for simplicity and versatility
OpenCV (Real-time body movement tracking): Modern technology component for enhanced functionality and performance
MediaPipe Pose (Push-up angle + rep detection): Modern technology component for enhanced functionality and performance
• NumPy & Pandas (Workout stats logging): Modern technology component for enhanced functionality and performance
• Streamlit (Frontend web interface): Modern technology component for enhanced functionality and performance
Firebase / Google Sheets (Workout history storage - optional): Google's mobile and web application development platform

System Architecture & Design

Architecture Type: Saas Application

Architecture Pattern: Modern Software Architecture with scalable design patterns

Scalability & Performance

Scalability Level: High - Enterprise-level scalability demonstrated

Security & Compliance

Security Level: Production-grade security with revenue validation

Security Technologies: Modern security practices and secure coding standards

Data Protection: Revenue-generating application with user data protection and privacy compliance

Integration & API Capabilities

API Technologies: Python API development with robust data processing capabilities

Integration Readiness: Production-ready for business integration and enterprise deployment

Development Environment & Deployment

Deployment Status: Production-ready for immediate deployment

Next Development Phase: <p>Add new features and improvements to increase user engagement</p><p>Run targeted marketing on social media to attract users</p><p>Offer premium / subscription-based features to monetize</p><p>Integrate additional automation or AI-based enhancements</p><p>Continuously update UI/UX and release new versions to keep users active</p>

Technical Summary

This saas project demonstrates advanced technical implementation using • Python (Core Logic),OpenCV (Real-time body movement tracking),MediaPipe Pose (Push-up angle + rep detection),• NumPy & Pandas (Workout stats logging),• Streamlit (Frontend web interface),Firebase / Google Sheets (Workout history storage - optional) with production-ready deployment. The technical foundation supports immediate business integration with modern security practices and scalable architecture.

Common Questions & Use Cases

How to Build a saas Project Like This

Technology Stack Required: • Python (Core Logic),OpenCV (Real-time body movement tracking),MediaPipe Pose (Push-up angle + rep detection),• NumPy & Pandas (Workout stats logging),• Streamlit (Frontend web interface),Firebase / Google Sheets (Workout history storage - optional)

Development Approach: Build a scalable software solution with modern architecture patterns and user-centered design.

Step-by-Step Development Guide

  1. Planning Phase: Define requirements, user stories, and technical architecture
  2. Technology Setup: Configure • Python (Core Logic),OpenCV (Real-time body movement tracking),MediaPipe Pose (Push-up angle + rep detection),• NumPy & Pandas (Workout stats logging),• Streamlit (Frontend web interface),Firebase / Google Sheets (Workout history storage - optional) development environment
  3. Core Development: Implement main functionality and user interface
  4. Testing & Optimization: Test performance, security, and user experience
  5. Deployment: Deploy to production with monitoring and analytics
  6. Monetization: Implement revenue streams and business model

Best Practices for saas Development

Technology-Specific Best Practices

• Python (Core Logic) Best Practices: Follow PEP 8 style guide, use virtual environments, implement proper exception handling, and optimize with profiling and caching.
OpenCV (Real-time body movement tracking) Best Practices: Follow modern development practices, implement proper error handling, use version control effectively, and optimize for performance and security.
MediaPipe Pose (Push-up angle + rep detection) Best Practices: Follow modern development practices, implement proper error handling, use version control effectively, and optimize for performance and security.
• NumPy & Pandas (Workout stats logging) Best Practices: Follow modern development practices, implement proper error handling, use version control effectively, and optimize for performance and security.
• Streamlit (Frontend web interface) Best Practices: Follow modern development practices, implement proper error handling, use version control effectively, and optimize for performance and security.
Firebase / Google Sheets (Workout history storage - optional) Best Practices: Follow modern development practices, implement proper error handling, use version control effectively, and optimize for performance and security.

General Development Best Practices

  • Code Quality: Write clean, maintainable code with proper documentation
  • Security: Implement authentication, authorization, and data protection
  • Performance: Optimize for speed, scalability, and resource efficiency
  • User Experience: Focus on intuitive design and responsive interfaces
  • Testing: Implement comprehensive testing strategies
  • Deployment: Use CI/CD pipelines and monitoring systems

Use Cases & Practical Applications

Target Audience & Use Cases

Business Use Cases: This project is ideal for businesses looking to generate revenue through proven monetization strategies. Perfect for entrepreneurs, startups, or established companies seeking saas solutions.

Comparison & Competitive Analysis

Why • Python (Core Logic),OpenCV (Real-time body movement tracking),MediaPipe Pose (Push-up angle + rep detection),• NumPy & Pandas (Workout stats logging),• Streamlit (Frontend web interface),Firebase / Google Sheets (Workout history storage - optional)?

This project uses • Python (Core Logic),OpenCV (Real-time body movement tracking),MediaPipe Pose (Push-up angle + rep detection),• NumPy & Pandas (Workout stats logging),• Streamlit (Frontend web interface),Firebase / Google Sheets (Workout history storage - optional) because:

  • Technology Synergy: The combination of • Python (Core Logic),OpenCV (Real-time body movement tracking),MediaPipe Pose (Push-up angle + rep detection),• NumPy & Pandas (Workout stats logging),• Streamlit (Frontend web interface),Firebase / Google Sheets (Workout history storage - optional) creates a powerful, integrated solution
  • Community Support: Large, active communities for ongoing development and support
  • Future-Proof: Modern technologies with long-term viability and updates

Competitive Advantages

  • Modern Tech Stack: • Python (Core Logic),OpenCV (Real-time body movement tracking),MediaPipe Pose (Push-up angle + rep detection),• NumPy & Pandas (Workout stats logging),• Streamlit (Frontend web interface),Firebase / Google Sheets (Workout history storage - optional) provides competitive technical advantages
  • Ready for Market: Production-ready solution with immediate deployment potential

Learning Resources & Next Steps

Learn • Python (Core Logic),OpenCV (Real-time body movement tracking),MediaPipe Pose (Push-up angle + rep detection),• NumPy & Pandas (Workout stats logging),• Streamlit (Frontend web interface),Firebase / Google Sheets (Workout history storage - optional)

To understand and work with this project, consider learning:

  • • Python (Core Logic): Python documentation, tutorials, and community resources
  • OpenCV (Real-time body movement tracking): Official documentation and community learning resources
  • MediaPipe Pose (Push-up angle + rep detection): Official documentation and community learning resources
  • • NumPy & Pandas (Workout stats logging): Official documentation and community learning resources
  • • Streamlit (Frontend web interface): Official documentation and community learning resources
  • Firebase / Google Sheets (Workout history storage - optional): Official documentation and community learning resources

Project Details

Project Type: Saas

Listing Type: Sell

Technology Stack: • Python (Core Logic),OpenCV (Real-time body movement tracking),MediaPipe Pose (Push-up angle + rep detection),• NumPy & Pandas (Workout stats logging),• Streamlit (Frontend web interface),Firebase / Google Sheets (Workout history storage - optional)

What's Included

domain,source_code,data,design,twitter,email

Reason for Selling

<p>I built this project as part of my portfolio and received great feedback. I’m now focusing on new projects and don’t have time to continue marketing or scaling this one.</p><p> I would like to pass it on to someone who can grow it further.</p>

Technical Architecture

Technology Stack & Architecture

This saas project is built using a modern technology stack consisting of • Python (Core Logic),OpenCV (Real-time body movement tracking),MediaPipe Pose (Push-up angle + rep detection),• NumPy & Pandas (Workout stats logging),• Streamlit (Frontend web interface),Firebase / Google Sheets (Workout history storage - optional). The architecture leverages these technologies to create a production-ready solution that can handle real-world usage scenarios.

Architecture Type: Saas - This indicates the project follows modern software architecture patterns.

Technical Complexity: Multi-technology stack requiring integration expertise

Business Context & Market Position

Business Model & Revenue Potential

This project represents a saas business opportunity with established market presence. The project currently generates $$0 in monthly revenue, demonstrating proven market demand and monetization potential.

Market Validation: With 50-120 monthly visitors, this project has achieved significant market traction and user adoption, indicating strong product-market fit.

Acquisition Opportunity: <p>I built this project as part of my portfolio and received great feedback. I’m now focusing on new projects and don’t have time to continue marketing or scaling this one.</p><p> I would like to pass it on to someone who can grow it further.</p> This presents an excellent opportunity for acquisition by someone looking to continue development or integrate the technology into their existing business.

Development Context & Timeline

Project Development Timeline

This project was created on November 5, 2025 and last updated on December 6, 2025. The project has been in development for approximately 1.1 months, representing 32.366706874456 days of development time.

Technical Implementation Effort

Implementation Complexity: High - The project uses 6 different technologies (• Python (Core Logic),OpenCV (Real-time body movement tracking),MediaPipe Pose (Push-up angle + rep detection),• NumPy & Pandas (Workout stats logging),• Streamlit (Frontend web interface),Firebase / Google Sheets (Workout history storage - optional)), requiring extensive integration work and cross-technology expertise.

Next Development Phase: <p>Add new features and improvements to increase user engagement</p><p>Run targeted marketing on social media to attract users</p><p>Offer premium / subscription-based features to monetize</p><p>Integrate additional automation or AI-based enhancements</p><p>Continuously update UI/UX and release new versions to keep users active</p>

Market Readiness & Maturity

Production Readiness: This project is market-ready and has been validated through real user engagement. The codebase is stable and ready for immediate deployment or further development.

Competitive Analysis & Market Position

Market Differentiation

Technology Advantage: This project leverages • Python (Core Logic),OpenCV (Real-time body movement tracking),MediaPipe Pose (Push-up angle + rep detection),• NumPy & Pandas (Workout stats logging),• Streamlit (Frontend web interface),Firebase / Google Sheets (Workout history storage - optional) to create a unique solution in the saas space. The technology stack provides cutting-edge technical implementation that sets it apart from traditional solutions.

Market Opportunity Assessment

Market Traction: With 50-120 monthly visitors, this project has demonstrated clear market demand and user adoption. This level of engagement indicates strong product-market fit and validates the business concept against existing market solutions.

Revenue Validation: The project's $$0 monthly revenue demonstrates proven monetization potential and market willingness to pay for this type of solution. This revenue performance positions it competitively against similar offerings in the market.

Competitive Advantages

  • Proven Market Success: Established user base and revenue stream provide immediate competitive advantage
  • Technical Maturity: Production-ready codebase with real-world testing and optimization
  • Market Validation: User engagement and revenue data prove market demand
  • Modern Technology Stack: • Python (Core Logic),OpenCV (Real-time body movement tracking),MediaPipe Pose (Push-up angle + rep detection),• NumPy & Pandas (Workout stats logging),• Streamlit (Frontend web interface),Firebase / Google Sheets (Workout history storage - optional) provides scalability, maintainability, and future-proofing

Pricing Information

Project Metrics

Average Monthly Visitors: 50-120

Average Monthly Revenue: $$0

Average Monthly Downloads: Currently 8–15 active testers

About the Creator

Developer: User ID 199995

Key Features

  • Built with modern technologies: • Python (Core Logic),OpenCV (Real-time body movement tracking),MediaPipe Pose (Push-up angle + rep detection),• NumPy & Pandas (Workout stats logging),• Streamlit (Frontend web interface),Firebase / Google Sheets (Workout history storage - optional)
  • Proven user base with 50-120 monthly visitors
  • Generates $$0 in monthly revenue
  • Ready for immediate acquisition

Frequently Asked Questions

What is this project about?

FitAI Smart Trainer is a saas project that FitAI Smart Trainer is an AI-powered fitness trainer that counts push-ups in real-time using a webcam. No wearable devices or sensors are needed — the system uses pose detection to understand body pos....

How much does this project cost?

This project is listed for sale at $negotiable USD. The price reflects the project's current revenue, user base, and market value.

What's included when I buy this project?

domain,source_code,data,design,twitter,email You'll receive everything needed to run and maintain the project.

Why is the owner selling this project?

<p>I built this project as part of my portfolio and received great feedback. I’m now focusing on new projects and don’t have time to continue marketing or scaling this one.</p><p> I would like to pass it on to someone who can grow it further.</p> This is a common reason for selling successful side projects.

What technologies does this project use?

This project is built with • Python (Core Logic),OpenCV (Real-time body movement tracking),MediaPipe Pose (Push-up angle + rep detection),• NumPy & Pandas (Workout stats logging),• Streamlit (Frontend web interface),Firebase / Google Sheets (Workout history storage - optional). These technologies were chosen for their suitability to the project's requirements and the developer's expertise.

What are the project's current metrics?

The project currently has 50-120 monthly visitors. It generates $$0 in monthly revenue. These metrics indicate the project's current performance and potential.

How do I contact the project owner?

You can contact the project owner through SideProjectors' messaging system. Click the "Contact" button on the project page to start a conversation about this project.

Is this project still actively maintained?

Since this project is for sale, the current owner may be looking to transfer maintenance responsibilities to the buyer.