Should I Build It Should I Build It
11 Jul 2025
Medical Health & Fitness

health tech platform for managing metabolic disease for patients and ...

...physicians

Confidence
Engagement
Net use signal
Net buy signal

Idea type: Freemium

People love using similar products but resist paying. You’ll need to either find who will pay or create additional value that’s worth paying for.

Should You Build It?

Build but think about differentiation and monetization.

Your are here

You're entering a crowded space with your health tech platform for managing metabolic disease. We found 15 similar products, which gives us high confidence that this is a valid area, but it also means you'll face stiff competition. Many existing apps focus on diabetes management, leveraging AI and CGM integration, but users are wary of AI inaccuracies, especially when health is involved. Given the 'Freemium' category designation, people like using these tools but aren't keen on paying upfront. You'll need to figure out what unique value proposition will make your platform stand out and convince users to open their wallets. Engagement is medium, reflected by the average number of comments, suggesting there's interest, but you need to convert that into active users and paying customers. Don't assume people will automatically pay; think strategically about your monetization strategy and value offering.

Recommendations

  1. Focus on a niche within metabolic disease management to differentiate yourself. Don't try to be everything to everyone. For instance, given user feedback on similar products, you might specialize in pre-diabetes management, offering a more comprehensive solution with personalized coaching than competitors.
  2. Given the wariness around AI accuracy, especially in healthcare, consider a hybrid approach. Use AI for data analysis and pattern recognition, but always have a human-in-the-loop for critical decision-making and recommendations. This can build trust and address accuracy concerns raised in the discussions about similar products.
  3. Prioritize integration with existing CGM devices and health platforms like Apple Health, as highlighted by positive user feedback on the "islet" app. Seamless data integration is crucial for user convenience and adoption. Make this a key feature from the outset.
  4. Given the freemium model, clearly define the value proposition of your premium features. What specific pain points will these features address that the free version doesn't? Consider offering personalized insights, advanced data visualization, or direct access to health professionals as premium perks.
  5. Explore team-based pricing or partnerships with clinics and healthcare providers. This could be a viable way to monetize the platform and provide value to a larger user base. Consider offering enterprise features that cater to these organizations to justify a higher price point.
  6. Actively solicit user feedback and iterate on your platform based on their needs and concerns. The criticism summary of similar products highlights the importance of user-friendliness and accuracy. Implement a robust feedback mechanism and prioritize bug fixes and feature improvements based on user input.
  7. Carefully consider the regulatory landscape and ensure compliance with relevant healthcare regulations, such as HIPAA. The discussion around the diabetes management app underscored the need for medical device certification and legal protection. Don't overlook these critical aspects.
  8. When choosing your app's title and keywords, prioritize clarity and discoverability, following the advice given to 'Enhance-d'. Use relevant terms that users are likely to search for when looking for a metabolic disease management platform. Also, take into account cross-locale keywords for improved search visibility.

Questions

  1. What specific metabolic diseases will your platform target initially, and how will you tailor the user experience to meet the unique needs of patients with those conditions?
  2. Given user distrust of AI in health-related apps, what specific measures will you take to ensure the accuracy and reliability of your AI-powered features, and how will you communicate these measures to users to build trust?
  3. What are the key performance indicators (KPIs) you will track to measure the success of your freemium model, and how will you iterate on your monetization strategy based on these KPIs?

Your are here

You're entering a crowded space with your health tech platform for managing metabolic disease. We found 15 similar products, which gives us high confidence that this is a valid area, but it also means you'll face stiff competition. Many existing apps focus on diabetes management, leveraging AI and CGM integration, but users are wary of AI inaccuracies, especially when health is involved. Given the 'Freemium' category designation, people like using these tools but aren't keen on paying upfront. You'll need to figure out what unique value proposition will make your platform stand out and convince users to open their wallets. Engagement is medium, reflected by the average number of comments, suggesting there's interest, but you need to convert that into active users and paying customers. Don't assume people will automatically pay; think strategically about your monetization strategy and value offering.

Recommendations

  1. Focus on a niche within metabolic disease management to differentiate yourself. Don't try to be everything to everyone. For instance, given user feedback on similar products, you might specialize in pre-diabetes management, offering a more comprehensive solution with personalized coaching than competitors.
  2. Given the wariness around AI accuracy, especially in healthcare, consider a hybrid approach. Use AI for data analysis and pattern recognition, but always have a human-in-the-loop for critical decision-making and recommendations. This can build trust and address accuracy concerns raised in the discussions about similar products.
  3. Prioritize integration with existing CGM devices and health platforms like Apple Health, as highlighted by positive user feedback on the "islet" app. Seamless data integration is crucial for user convenience and adoption. Make this a key feature from the outset.
  4. Given the freemium model, clearly define the value proposition of your premium features. What specific pain points will these features address that the free version doesn't? Consider offering personalized insights, advanced data visualization, or direct access to health professionals as premium perks.
  5. Explore team-based pricing or partnerships with clinics and healthcare providers. This could be a viable way to monetize the platform and provide value to a larger user base. Consider offering enterprise features that cater to these organizations to justify a higher price point.
  6. Actively solicit user feedback and iterate on your platform based on their needs and concerns. The criticism summary of similar products highlights the importance of user-friendliness and accuracy. Implement a robust feedback mechanism and prioritize bug fixes and feature improvements based on user input.
  7. Carefully consider the regulatory landscape and ensure compliance with relevant healthcare regulations, such as HIPAA. The discussion around the diabetes management app underscored the need for medical device certification and legal protection. Don't overlook these critical aspects.
  8. When choosing your app's title and keywords, prioritize clarity and discoverability, following the advice given to 'Enhance-d'. Use relevant terms that users are likely to search for when looking for a metabolic disease management platform. Also, take into account cross-locale keywords for improved search visibility.

Questions

  1. What specific metabolic diseases will your platform target initially, and how will you tailor the user experience to meet the unique needs of patients with those conditions?
  2. Given user distrust of AI in health-related apps, what specific measures will you take to ensure the accuracy and reliability of your AI-powered features, and how will you communicate these measures to users to build trust?
  3. What are the key performance indicators (KPIs) you will track to measure the success of your freemium model, and how will you iterate on your monetization strategy based on these KPIs?

  • Confidence: High
    • Number of similar products: 15
  • Engagement: Medium
    • Average number of comments: 8
  • Net use signal: 4.9%
    • Positive use signal: 15.0%
    • Negative use signal: 10.1%
  • Net buy signal: -5.6%
    • Positive buy signal: 0.8%
    • Negative buy signal: 6.4%

This chart summarizes all the similar products we found for your idea in a single plot.

The x-axis represents the overall feedback each product received. This is calculated from the net use and buy signals that were expressed in the comments. The maximum is +1, which means all comments (across all similar products) were positive, expressed a willingness to use & buy said product. The minimum is -1 and it means the exact opposite.

The y-axis captures the strength of the signal, i.e. how many people commented and how does this rank against other products in this category. The maximum is +1, which means these products were the most liked, upvoted and talked about launches recently. The minimum is 0, meaning zero engagement or feedback was received.

The sizes of the product dots are determined by the relevance to your idea, where 10 is the maximum.

Your idea is the big blueish dot, which should lie somewhere in the polygon defined by these products. It can be off-center because we use custom weighting to summarize these metrics.

Similar products

Relevance

The App I Built to Help Manage My Diabetes

18 Nov 2024 Artificial Intelligence Productivity Health & Fitness

Hi HN,I’m Joshua, a student, and I’m excited (and a little nervous) to share something deeply personal that I’ve been working on: Islet, my diabetes management app powered by GPT-4o-mini. It’s now on the App Store, but I want to be upfront—it’s still very much in its early stages, with a lot more to go.I was diagnosed with Type 1 diabetes while rowing competitively, and that moment changed everything. It wasn’t just the practical challenges of managing insulin, carb counts, and blood sugars; it fundamentally shifted how I see myself and the world. It forced me to slow down, prioritise my health, and take control in ways I never had to before. My outlook on life became more focused on resilience, adaptability, and finding solutions to problems that truly matter.This app started as a pet project over the summer, a way to see what I could create using ChatGPT and explore the potential of LLMs to help with real-world challenges. At first, it was just about making my own diabetes management easier—understanding patterns in blood sugars, planning meals, and adjusting routines. But as I worked on it, I realised it could do more.Right now, Islet offers personalised meal suggestions, tracks activity, and provides basic insights based on the data you enter. It’s far from complete. Even so, the process of building Islet has already taught me so much about how powerful AI can be in creating personal, meaningful tools.This project is deeply tied to how my diagnosis changed me. It’s about more than managing diabetes, it’s about showing how anyone, even a student experimenting over the summer, can use AI to potentially solve real, personal problems. I believe tools like LLMs have the power to democratise solutions for all, making life just a bit easier for all of us.If you’re curious, you can check it out here: https://apps.apple.com/gb/app/islet-diabetes/id6453168642. I’d love to hear your thoughts what works, what doesn’t, and what features you think would make it better. Your input could help shape the next steps for Islet.Thanks for reading !joshua

The Show HN product, likely a diabetes management app involving AI, received mixed feedback. Users praised its appearance and achievement but expressed concerns about AI reliability, especially in healthcare. There were references to the Therac-25 incident and caution advised by a doctor. Questions were raised about the app's unique value, medical device certification, and data usage. Some users were curious about specific features like photo recognition for carb counting, which was criticized for inaccuracy. The app's potential release on GitHub, its non-availability on the App Store, and the need for updates to the Privacy Policy were also discussed. There were offers to share experiences and requests for Android compatibility. Comments on diet and diabetes management were mixed, with some advocating for low-carb diets and others emphasizing the need for insulin regardless of diet.

Users expressed concerns about the product's medical safety, particularly regarding insulin delivery and the accuracy of AI-generated advice for diabetics. Criticisms include the potential need for medical device certification, unclear AI involvement, and the risk of inaccurate photo recognition for food. The app's lack of availability on certain platforms, unclear data usage, and the necessity for legal protection due to possible incorrect responses were also mentioned. Some users questioned the app's unique value and feasibility, while others criticized its style and the lack of a clear release plan.

https://news.ycombinator.com/user?id=je42

However, if you dont have carb info, the alternative is to judge yourself. Your own model may be better than gpts model, though. I would use GPTs output and at least look at it on a case by case basis

https://news.ycombinator.com/user?id=8mobile

Hi Joshua,I am so sorry to hear about your diagnosis, it happened in our family and it changed our lives. I will definitely try your app because I am curious if AI can improve diabetes management. Does the app support both mmol/L and mg/dL? Have you had any limitations with iOS? Do you have an Android version in mind? Thanks for your efforts

https://news.ycombinator.com/user?id=trialskid1986

As a new diagnose T1D I love this!I signed up for the free week trial to test out some of the AI features. When I asked it to analyze my week the numbers weren’t very accurate compared to my graphs inside the app.If you need help troubleshooting I’d be more than happy to help

https://news.ycombinator.com/user?id=leereeves

Looks great. I'd love to try an Android version.

https://news.ycombinator.com/user?id=pimeys

There's been one for years already. Instead of sending your data to ChatGPT, it uses multiple scientific models to calculate your insulin resistance, basal dose and can give you an accurate amount of insulin to dose based on the number of carbs you input. What the Android app can do and iOS makes very hard is to control your pump and close the loop. It is illegal to distribute health apps in binary form if they control your pump, but very much legal in source code form. Try it out:https://androidaps.readthedocs.io/en/latest/This is a life-changing app. It lowered my A1c values from around 8% to 5.5%. What is so special with Android is how easy it is to side-load apps, so you can compile AndroidAPS by yourself and keep using it. In Apple ecosystem you need the developer subscription and you also need to reinstall the app every now and then. There is still the Loop app if any iOS users want to try, but this complication from Apple has just pushed me to Android ecosystem for the past decade already.https://loopkit.github.io/loopdocs/

https://news.ycombinator.com/user?id=tigerwash

There is also iAPS, the AAPS-version but for Apple Devices; also take a look at Trio.https://iaps.readthedocs.io/en/main/https://docs.diy-trio.org/But I like using Loop/LoopKit due its simple interface.

https://news.ycombinator.com/user?id=je42

My son (13) and I are also using AAPS for roughly 3 years now. The app does not look styled, however after taking the initial hurdle to find our way around in the app, it is greatly appreciated. Integrates nicely with Xdrip ( anf others)

https://news.ycombinator.com/user?id=pimeys

It is a life-saver. Learn it once, and it is the most important tool in your diabetic toolbox.

https://news.ycombinator.com/user?id=didgeoridoo

> GluCoPilotI’m dead I love it.

https://news.ycombinator.com/user?id=schusterlich

Hey Joshua, Amazing work with the app and a sad welcome to the pancreatically challenged club from a long term member!I love the app and feel we could have quite some similarities, I too undertook the effort to create a solo-diabetes app for the community, called "Diabetes Cockpit" - i think yours looks much prettier though <3Would love to connect and have a coffee - tried the contact on the website but its not implemented yet i think ;PSo maybe you just get in touch via schusterlich@gmail.com if you are up for it, i would be happy!Really good work! Best, Lukas

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185
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islet - A personalized health journal app

07 Oct 2024 Medical Quantified Self Health & Fitness

Islet is designed for CGM users to better understand blood sugar trends. It provides insights, glucose impact scores, and activity tracking to help you manage how meals, exercise, and daily activities affect your levels, making glucose control easier.

Islet is lauded as a helpful and promising tool, especially for CGM users, in managing and controlling blood sugar levels. Users appreciate its integration with Apple Health, activity tracking, and glucose insights. Suggestions include meal suggestions based on glucose trends, more visualization options, unified health and habit tracking, and reminders for logging meals and activities. The app is considered a potential game-changer that simplifies the tracking process, empowering users to control their health. Future updates are anticipated, and users are congratulating the launch.

Users suggest meal integrations based on glucose trends to improve the product's value. Several users noted the need for improved user-friendliness through features like reminders and notifications. There is also a desire for more robust visualization options, specifically longer-term glucose trend charts. Finally, some users feel that the writing quality could be improved.

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149
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Unswt – Free AI Sugar Tracker Using Meal Photos

20 Sep 2024 Artificial Intelligence Health & Fitness

Hey HN,We’ve built unswt, a free AI-powered sugar tracker that helps users manage their blood sugar by simply snapping a photo of their meal. No devices, no subscriptions—just straightforward feedback on how your food impacts your glucose levels.How It Works: Snap a photo of your meal. Get instant feedback on predicted glucose levels, macro/micro breakdown, and how the food impacts your body. Why We Built It: Managing blood sugar can be tough, especially with so many processed foods and busy lifestyles. We wanted to make it easier for people to understand their body's reaction to food without needing expensive hardware. We’re collaborating with Johns Hopkins cardiology and endocrinology teams and GW nutrition AI PhDs to ensure the science behind it is solid.Why Free? We believe in making this resource accessible to everyone. No hidden fees, no premium features—just a free tool to help you make better health decisions.We Need Your Feedback: We’re still early and would love to get feedback from the HN community. What’s working? What’s not? What features would be useful? You can try it for free, and any feedback (good or bad) would help us improve the app.Check it out: unswt.comLooking forward to your thoughts!

Users expressed mixed reactions to the product. One user appreciated the impact but noted they don't own a phone. Several users questioned the usefulness compared to existing methods and raised concerns about the AI's accuracy, particularly in identifying food items like mistaking fondant cake for a hamburger. There was a suggestion to use nutrition facts rather than relying on AI for image recognition, and a general distrust of AI was mentioned.

Users question the product's usefulness compared to existing methods, expressing concerns over AI accuracy, specifically doubting its ability to identify food correctly. There's skepticism about the necessity of AI for image recognition and a general lack of trust in AI.

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urth by trst - No matter the pre-diabetes diagnosis, we've got you covered!

19 Apr 2024 Health Tech Health & Fitness

Welcome to urth – your trst-ed app, health coach, and partner in managing prediabetes, diabetes, or insulin resistance. With cutting-edge CGMs, behavioral science, and circadian rhythms, urth empowers you to control your health through simple habit changes.

Urth is lauded as an awesome and comprehensive tool for managing prediabetes and diabetes, offering features like CGM, circadian rhythm tracking, habit tracking, and insights. It's described as a proactive, free app integrating technology and behavior science for prediabetes management. There's interest in the platform's availability and details about its digital coach.

Users expressed concerns regarding the lack of clarity around CGM integration and the personalization of coaching features. Additionally, one user reported that the second link provided was broken and needed fixing.

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Introducing an AI Health Guidance App for Managing Chronic Conditions.

31 Oct 2024 Health Medical Artificial Intelligence Health & Fitness

I’m excited to share that I’m building an AI health guidance app aimed at helping individuals manage chronic conditions and take control of their health. Our goal is to simplify complex medical reports, provide personalized health advice, and offer expert AI tips to help users avoid unnecessary doctor visits.I would love to get your feedback! If you’re interested in exploring how this app can support you or someone you know, please take a moment to check it out. Your insights will be invaluable as we work to make this tool better for everyone facing similar challenges.

Building AI health app for chronic condition management.

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Lingo - Biosensor CGM + App = Avoid Type 2 Diabetes

13 Oct 2024 iOS Biohacking Health & Fitness

Biosensor decodes your personal glucose response to food and exercise. Ppp translates your data into something you can understand and act upon. Coaching program is designed by experts to help you build habits and adjust your nutrition. No subscription, No Rx.

Lingo CGM helps track glucose levels; cheap, no subscription.

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GlucoLog - Diabetes Tracking Diary

08 Nov 2024 Health Health news Health & Fitness

The ultimate app for individuals managing diabetes or tracking their blood sugar levels. Designed to be user-friendly, this app provides seamless logging, tracking, and analysis of glucose data, ensuring you have everything you need at your fingertips.

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Enhance-d - The exercise app for the diabetes community

20 Nov 2024 Health Medical Health & Fitness

Enhance-d is an App developed to support people with diabetes in managing their condition through exercise. The goal is to make continuous glucose monitoring data actionable around exercise and create the world’s largest online diabetes community

The Product Hunt launch is being congratulated, with particular emphasis on the app's potential impact on bridging exercise and diabetes management. Users appreciate its simplification of diabetes management through exercise and community support. A suggestion was made to prioritize keywords in the app title to improve discoverability.

The Product Hunt launch received criticism regarding the app's title, which was perceived as too minimal and lacking cross-locale keywords for improved search visibility. Additionally, a user inquired about the possibility of sharing glucose monitoring data within the app's community.

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