COLAB27 - Mobile App

Swapfit AI

Your Adaptive Fitness Ally. Our AI app powered offers exercise substitutions and precise muscle group targeting, empowering you to maximise results

With SwapFit Ai, you're never limited by equipment availability or stuck with exercises that don't suit you. Our innovative app powered by AI offers exercise substitutions and precise muscle group targeting, empowering you to tailor your workouts to your individual preferences and maximize results. Say goodbye to workout plateaus and hello to a more effective, personalized fitness journey with SwapFit AI.

Problem Background  

We focused our attention on the fitness problem space due to its significant market size, boasting a total revenue of $30.6 billion in 2023 according to Statistica. Additionally, we shared a passion for the well-being of its users. While there were various directions we could have pursued within this space, ranging from yoga to supplement experiences to swimming, we deliberately chose to tackle resistance and strength training due to the high levels of user passion and engagement, as well as the potential for innovation with AI within this subset.

To gain deeper insights, we conducted 7 interviews and received 8 survey responses. This approach allowed us to uncover user pain points and validate or invalidate existing hypotheses.

Our initial hypothesis pinpointed the intermediate fitness enthusiast as our ideal user persona, driven by their passion for growth and their identifiable pain points. Conversely, beginners demonstrated lower levels of motivation, while experts often served as fitness coaches themselves.

We identified individuals like Alex within the intermediate fitness user category who possessed specific needs, signaling an opportunity for us to deliver significant value to our users with AI.

Traditional approaches to fitness planning frequently result in frustration and stagnation, as users find themselves limited by equipment availability and constrained by exercises that fail to align with their goals. Despite the abundance of fitness resources available, finding suitable exercise substitutions and precisely targeting specific muscle groups remains a daunting task for many users.

This lack of adaptability not only hinders progress but also diminishes motivation, leading to disengagement and suboptimal results in the long run. To address this pressing issue, there is a critical need for a solution that leverages AI  technology to provide personalized and adaptable fitness guidance for our users.

Research Insights

User Pain Points
  1. Adapting exercises based on the availability of gym equipment, whether it's in use or accessible.
  2. Many users struggle to find a workout plan, often leading them to skip it altogether out of frustration.
  3. Overcoming equipment inaccessibility due to restrictions such as height.
  4. Adapting exercises to accommodate injuries and ensure safe, effective workouts.

Inferred Pain Points
  1. Generating workout plans has traditionally been a tedious process. Some individuals opt to outsource this task to trainers, while others spend hours scouring social media for suitable plans.

Solution Explanation

When thinking about the designs of how we were going to solve the user's problem of finding a substitute exercise, we knew that we wanted to streamline their current process mentioned in the user interviews. 

Their process was time consuming, in that it involved a lot of googling and searching YouTube. In addition, people were cross referencing the information to ensure the substitute exercise was targeting the same muscles as the exercise they were trying to replace.

Approaching this problem meant that we had to consider many factors, such as technical constraints, Co.Lab’s timeframes, and business goals. Once we narrowed these down, we were able to determine a possible solution. Feel free to take a tour of our exploration below:

Low Fidelity Mockups

Swap Exercise: 

Users are invited to enter the exercise they’re trying to replace so that SwapFit may suggest a substitute that will target the same muscle group.

Select Equipment:

Users can choose which equipment is around them so they will be recommended relevant exercises.

Select Substitute:

Users will be shown a list of substitute exercises based on the exercise they entered and the equipment they selected.

Exercise Information:

In the event where users are unfamiliar with the name of the exercise, they will be shown a video along with instructions on how to perform the exercise.

Swap Another Exercise:

If users want to find another substitute exercise, they can select the search icon. Once they enter in the exercise they want to replace they’ll be prompted to repeat the flow. 

Final MVP 

Check out the Prototype

Design Learnings

Results from the usability tests revealed that the initial designs were on the right track! At this point, our team moved forward with addressing tasks in the backlog. We can now design and implement the other need addressed in the user interviews, which was informing people which muscle group the exercise targeted.

To keep things categorized, we decided to divide the exercise information page into two tabs. In addition to users being shown the video demonstration and instructions, they can now view which muscle group the exercise targets.

Those of you in the audience who are seasoned weightlifters noticed that just the hamstrings are highlighted, as opposed to the inclusion of glutes and other secondary muscles. Although this is a temporary limitation, we are currently working on displaying the full list of targeted primary and secondary muscles for future development. We’re excited to incorporate this so users have full access to having a knowledgeable & confident workout.


Designing the logo was initially tricky, as I wanted to incorporate the concept of switching exercises and weightlifting. While there were many ideas that reflected the function of SwapFit, our team eventually landed on what we believe was the simplest and effective imagery.

Implementation Details 

Future Steps

We will not be continuing the project full time, however we will be making some updates and working on it on weekends.

Here are some of our future features

  • App Publishing (Play Store, App Store)
  • User Login, Saved Personal information
  • Workout Planner
  • Goal Tracker
  • Leaderboard for User retention
  • Workout community (Share your gains!)

Go-To Market Strategy

In our endeavor to effectively plan and execute our Go-To-Market (GTM) strategy for Swap Fit AI, we have adopted the widely acclaimed SOSTAC marketing framework. SOSTAC, which stands for Situation Analysis, Objectives, Strategy, Tactics, Action, and Control, provides a comprehensive and structured approach to developing and implementing marketing plans.

By leveraging this framework, we aim to systematically assess market dynamics, set clear objectives, devise strategic initiatives, implement tactical plans, take decisive actions, and maintain control over our marketing efforts. This introduction sets the stage for a methodical and disciplined approach to driving the success of Swap Fit AI in the competitive fitness app landscape.

1. Situation Analysis:
  • Identify the market opportunity: The $30.6 B fitness industry is growing, with a significant portion of the population seeking personalized AI fitness solutions.
  • Evaluate competitors: Analyze existing fitness apps and their offerings to identify gaps and opportunities for differentiation with AI for personalization.
  • Assess internal capabilities: Review Swap Fit AI's resources, including technology, team expertise, social circle and budget, to determine readiness for launch.

2. Objectives:
  • Launch Swap Fit AI's MVP within x weeks.
  • Acquire 1,000 users within the 6 months of launch.
  • Achieve a user retention rate of 40% after 3 months.
    Generate positive user feedback and ratings to build brand credibility.

3. Strategy:
  • Target Audience: Intermediate fitness enthusiasts aged 25-40 who seek personalized substitute exercise.
  • Positioning: Position Swap Fit AI as your adaptive fitness ally powered by AI technology, offering personalised coaching and data-driven insights to make all your fitness goals a reality.
  • Product Offering: Highlight features such as tailored substitutes recommendations, progress tracking, and motivational support.
  • Pricing: Offer a freemium model with basic features available for free and premium features accessible through subscription at $9.99 after we hit 1000 users.

4. Tactics
  • Product Development: Refine the MVP based on user feedback and internal testing to ensure usability and functionality.
  • Marketing Channels: Utilize social media and posting on our personal pages, launching in communities on reddit and facebook, influencer partnerships,  to reach the target audience.
  • User Acquisition: Offer early access invitations and referral incentives to encourage sign-ups and word-of-mouth promotion.
  • User Engagement: Implement gamification elements, personalized notifications, and community features to enhance user engagement and retention.
  •  Customer Support: Provide responsive customer support channels to address user inquiries and issues promptly

6. Action
  • Develop a detailed launch timeline with specific tasks and deadlines for each stage of the GTM strategy.
  • Assign responsibilities to team members and allocate resources effectively to execute the plan.
  • Monitor progress closely and adjust tactics as needed based on real-time feedback and performance metrics.

7. Control
  • Regularly track key performance indicators (KPIs) such as user acquisition, retention, conversion rates, and customer satisfaction scores.
  • Conduct ongoing market research and competitor analysis to stay informed about industry trends and evolving customer preferences.
  • Conduct post-launch reviews to evaluate the effectiveness of the GTM strategy and identify areas for improvement in future marketing campaigns.


Product Manager Learnings:

Yoofi Annan

Throughout my tenure as a Product Manager at Co.Lab, I refined the following skills:

1. Developing expertise in managing the development of AI products, incorporating cutting-edge technology into our solutions.

2. Proficiently identifying and prioritizing the pain points experienced by our users, ensuring that our product addresses their most pressing needs effectively.

3. Skillfully defining the minimum viable product (MVP) features by analyzing user stories and requirements, guiding the team towards delivering the most essential functionalities.

4. Successfully leading a team through the process of building an MVP that offers effective solutions to users' pain points, fostering collaboration and synergy among team members.

5. Implementing an iterative approach to product development, leveraging initial user feedback on projects like Swap FIT AI to guide ongoing iterations and improvements, ensuring continuous enhancement of the product's value proposition.

Designer Learnings:

Jenny Ngo

Communicate designs early and often!

Working in a team allowed me to experience the advantage of discussing design iterations early within product development. Designers can put together visually appealing interfaces and a number of functionalities, however the implementation of those interfaces are not always technically feasible. Inorder to keep things efficient and inexpensive, I sketched out multiple ideas for each screen with pen and paper.

This method allowed me to quickly communicate possible solutions with the developers in order to gain their feedback. Once I received their feedback, I was able to create the digital designs with confidence.

Developer Learnings:

Sebastien Dupont

During my 8 weeks at Co.Lab, I underwent a transformative learning journey. I delved into React Native, mastering its intricacies and honing my skills in mobile app development. Customizing Google Gemini AI became second nature, as I integrated it into projects, leveraging its power for enhanced functionality. My understanding of API calls deepened, allowing me to integrate external data sources and services into my applications.

Furthermore, I integrated YouTube videos within apps, enriching user experiences. Navigating through app interfaces became intuitive as I grasped the nuances of in-app navigation, culminating in a comprehensive skill set poised for real-world application.

Developers Learnings:

Tom Garrett


Collaborating on this project was a valuable learning experience that encompassed teamwork, creative problem-solving, and technical skill development. Working primarily on the front-end with React Native framework allowed me to deepen my understanding of mobile app development and utilize style sheets effectively.

Additionally, I gained further insight into API integration, enhancing my ability to connect front-end interfaces with back-end functionality. This experience reinforced the importance of collaboration, patience, and alignment with team goals, while also expanding my technical capabilities in app development.

Full Team Learning

1. Cross-Functional Collaboration

Through regular communication and joint problem-solving sessions, we maximized our collective expertise to overcome challenges and deliver a cohesive product.

2. Agile Project Management Principles 

Practices such as daily stand-up meetings, backlog grooming, and regular retrospectives facilitated transparency, alignment, and continuous improvement throughout the bootcamp project.