Integrations

Connect Proov Insight via Spike API

Connect to Proov Insight via the Spike Wearables API to access users' hormone and fertility data. Retrieve metrics such as progesterone metabolite (PdG) levels, estrogen markers (E1G), luteinizing hormone (LH), follicle-stimulating hormone (FSH), and personalized ovulation scores that users already track, enhancing your app’s functionality and reducing manual data entry.

Book a demo
200+ healthcare organizations work with Spike

Integrate Proov Insight data into your app in 3 easy steps with Spike Wearables API

Get data from Proov Insight into your app via Spike Wearables API with just a few lines of code. Save months of in-house development and maintenance.

Access your account in Spike platform

Your dedicated Implementation Engineer will guide you and help start smoothly.

Establish secure connection

Use examples in multiple programming languages to implement secure authentication.

Set up webhooks for real-time updates

Enable automatic data delivery to your application whenever new data becomes available

Get real-time data and historical insights from any device with Spike Wearables API

Access historical data

Acquire historical data through HTTP requests.

Specify the duration and retrieve past health metrics for comprehensive health trend insights.

Track improvements and analyze patterns.

Build AI insights with MCP

Use Spike MCP to add AI insights to your app, working directly with data from Proov Insight.

Automatically fetch, analyze, and interpret data from all your connected devices.

Spike MCP server handles authentication, data retrieval, and formatting.

Who can leverage Proov Insight data?

Proov Insight is a fertility and hormone tracking platform that offers at-home test kits and a mobile app to monitor key hormones like progesterone (PdG), luteinizing hormone (LH), and follicle-stimulating hormone (FSH).

Book a demo
Docs

Fitness & workout apps

Fitness and workout apps can integrate Proov Insight data to deliver richer user experiences through enhanced tracking capabilities and personalized recommendations.

Sleep tracking apps

Proov Insight data support sleep apps managing hypertension and sleep apnea, enhancing health monitoring and management.

Nutrition and diet apps

Apps can use Proov Insight data related to nutritional intake to provide personalized dietary recommendations, track adherence to dietary goals, and offer insights into overall nutritional habits.

Mental health apps

Proov Insight data can be used to track emotional well-being and integrate mental health insights into overall health assessments.

Medical and health monitoring apps

Proov Insight provides data on vital signs and health metrics, which can be used to monitor overall health, manage chronic conditions, and integrate insights into personalized care plans.

Schedule a quick demo

We’d be happy to give you a quick intro on how you can leverage Spike Health 360 API.
We have same-day or next-day slots available. Just pick a convenient time for you.

Book a demo

Hear From our Customers

Learn how companies worldwide are using Spike to transform everyday health and wellness.

"It's the best support we have from any provider. We're integrated in Slack, and despite time zone changes, that hasn't become an issue."

Nicolas Lasso
CTO
Read case study

"Spike gave us a huge shortcut. It would've taken months to get wearables working right — and even then, we'd still have to maintain them. Now we just build on top."

Kevin Lam
Principal Software Engineer
Read case study

“Spike API enabled us to access and manage data from various wearables efficiently. The fact that Spike does not store user data was a crucial factor in our decision, ensuring our commitment to data privacy and security.“

Ciara Ferguson
Chief Data Scientist
Read case study

"With Spike API, we’ve been able to integrate diverse wearable data, offering our users more precise and actionable insights. This has improved the accuracy of our training recommendations and user satisfaction."

Brian Rosetti
Founder
Read case study