DTTP AI PM

AI-Powered Health Assistant

Transforming health data into actionable insights with AI-driven analysis and personalized recommendations.

Product Experience

Problem Space

Problem Statement

How might we enhance the iPhone Health App by providing AI-driven insights, proactive health monitoring, and personalized recommendations to help users better understand their health data and take meaningful actions to improve their well-being?

Problem Background

  • Many users track their health data but struggle to interpret trends.
  • Users managing chronic conditions lack timely alerts on potential health risks.
  • Current solutions lack proactive, AI-powered insights that guide users toward healthier decisions.

Research Insights

User Pain Points:

  • Difficulty in analyzing health trends from raw data.
  • Lack of consistency in tracking health habits.
  • Uncertainty about how to act on health insights.

Supporting Data:

  • 83% of users check the Health App weekly but struggle with data interpretation.
  • 100% of survey respondents expressed interest in AI-generated insights.
  • 60% of users are open to AI-driven health recommendations.

Feedback

  • User testing revealed that AI-generated health summaries improved engagement and understanding.
  • Beta testers reported increased motivation to maintain healthier habits due to AI-driven reminders.

Landing on the Solution

  • Based on our target users’ pain points, we designed an AI-powered assistant that provides:
    • Health Insights & Summaries: AI-generated reports on sleep, activity, and heart rate trends.
    • Anomaly Detection & Alerts: Identifies potential health risks and prompts users to take preventive action.
    • Personalized Recommendations: AI-driven suggestions for lifestyle improvements.
    • Voice & Chat Integration: Hands-free access to AI-powered health insights.
    • Automated Health Reports: Shareable insights for medical consultations.

User Flows & Mockups

Future Steps

  • Expand AI capabilities to include predictive health trend analysis.
  • Enhance integration with Apple Watch and third-party health apps.
  • Conduct further user testing to refine AI-generated insights and alerts.

Images & Visuals

Learnings

Product Manager Learnings:

Antonia McDonald

This learning experience with Co.Lab has been nothing short of amazing. It has been a great opportunity through which I was able to learn and apply key Product Management principles. I have included below a summary of some the experiences and insights I gained:

  • Leading AI-driven product development requires balancing technical feasibility with user expectations.
  • User feedback is essential in refining AI-generated recommendations for accuracy and reliability.
  • Iterative prototyping and usability testing significantly improved product-market fit.

Final Thoughts:
The AI-Powered Health Assistant bridges the gap between raw health data and actionable wellness insights, enhancing user engagement and proactive health management within the iPhone Health App.

Designer Learnings:

Designer Learnings:

Jo Sturdivant

  1. Adapting to an Established Team: Joining the team in week 6 of 8 was challenging, as I had to quickly adapt to existing workflows, dynamics, and goals. This mirrors real-world situations where you often integrate into teams mid-project, and flexibility is essential.
  2. Work-Blocking for Efficiency: With only two weeks to complete the project, I learned the importance of a structured work-blocking system. This approach allowed me to manage my time effectively and meet deadlines under pressure.
  3. Making Data-Driven Design Decisions: Unlike my past projects, I had to rely on research conducted by others. This was a valuable experience in using pre-existing data to guide design decisions, helping me focus on the core insights without starting from scratch.

Developer Learnings:

Developer Learnings:

Vanady Beard

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As the back-end developer, I learned how important it is to create efficient and reliable systems that support the entire application. This experience also taught me the importance of optimising the database and ensuring the backend is scalable and easy to maintain.

Developer Learnings:

Stephen Asiedu

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As a back-end developer, I've come to understand the importance of being familiar with various database systems and modules. This knowledge enables me to build diverse applications and maintain versatility in my work. I've also learned that the responsibility for making the right choices rests on my shoulders, guided by my best judgement.

Developer Learnings:

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Developer Learnings:

Maurquise Williams

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  1. Process of Creating an MVP: Developing a Minimum Viable Product (MVP) taught me how to focus on delivering core functionalities balancing between essential features and avoiding scope creep.
  2. Collaboration in a Real-World Tech Setting: This experience taught me how to collaborate efficiently in a fast-paced tech environment, keeping the team aligned and productive, even while working remotely across time zones.
  3. Sharpening Critical Thinking and Problem-Solving Skills: This experience honed my ability to think critically and solve problems efficiently. By tackling challenges and finding quick solutions, I sharpened my decision-making and troubleshooting skills in a dynamic, real-world setting.

Developer Learnings:

Jeremiah Williams

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All in all this experience was very awesome I learned that in coding with others being transparent is key

Developers Learnings:

Justin Farley

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I learned how important communication is when working with a team. Communication provides understanding, advice, ideas, and much more. While working with the product team, I’ve found that communication keeps everything flowing smoothly. Working with a team also showed me that every member brings something different to the table and we all have to work together in order to align and meet our end goal.

Full Team Learning