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Metriport – Open-source universal API for health data

Hacker News

Metriport – Open-source universal API for health data

Hey HN, we’re Colin and Dima, founders of Metriport ( https://metriport.com/ ). We help digital health companies access and manage user health and medical data, through an open-source and universal API. Today we're launching our open-source Health Devices API, which allows companies to gain access to their users’ health data from various wearables, RPM devices, and mHealth apps. You can check out the public Github repo here: https://github.com/metriport/metriport For developers in the health data space, building integrations to various data sources is a huge pain, as it means wrangling different data formats, gaining access to the APIs in the first place, and ultimately spending precious developer resources building out data pipelines. We solve this pain for you through our open-source API, which is quick and easy to get started with (see: https://docs.metriport.com/getting-started/connect-quickstar... ). Out of the box, our Health Devices API supports integrations with Fitbit, Oura, Whoop, Withings, and Cronometer. We plan to add many more, including Garmin, Apple Health, and Google Fit in the near term. We work closely with our customers, so if there’s an integration you need, we’re more than happy to build it into our API. Because we’re open-source, you can also fork our code and build your own custom integrations. Getting started is simple. To start getting data from your users: 1) Create a developer account and generate an API key: https://dash.metriport.com/ 2) Set up our client on your server and initialize it with your API key: https://docs.metriport.com/getting-started/connect-quickstar... 3) Link the Metriport Connect widget into your app. This pre-built widget makes it easy for your users to connect all their data sources into your application. Now you’re ready to start accessing your users’ health data from their sources they’ve connected. We also offer a hosted SaaS solution with usage-based pricing, with no minimum platform fees. We believe this will open doors to a wide range of early stage companies and help drive innovation in the digital health industry. While we’re excited to be launching this product today and be the first open-source Health Devices API of its kind, we’re also really looking forward to sharing our Medical API with you in the coming months. You can find out more about that here: https://metriport.com/medical We can’t wait to see how this API is used and what it helps companies develop. Please don’t hesitate to reach out if you have any questions, and happy developing!

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Indie HackersFits the IH revenue-focused audience · Strong signals: supports, started, including · Missing: reddit linkedin, podcasting, created
91%91% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Product HuntOn track for Day 1 leaderboard · Strong signals: apple, google, apps · Missing: mac, agents, macos
85%85% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: excited, ide, pipe · Missing: https docs, just released, exist
77%77% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRFits verified-revenue profile · Strong signals: apps, month, google · Missing: mobile apps, ios, personal
50%50% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform, host, users · Missing: plus, intuitive, reviews
35%35% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: saas · Missing: arr, mrr, revenue
20%20% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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