Spike

Generative AI API

“Health Data Interpretation as-a-service”:
a cutting-edge solution for digital health startups. Our advanced machine learning algorithms interpret end-user-specific data from wearables, fitness trackers, and IoT devices to provide daily insight in an informal conversational format. Observations are designed only for indicative and not medical-advisory use.

Raw Data Input

  • Sleep duration and sleep stages (light, deep, REM)
  • Heart Rate Variability (HRV)
  • Heart rate (HR)
  • Fitness Activity
  • All of the data through Spike API network of wearables

Output

  • Text based observations
  • Text bases recommendations
  • Charting (beta)

Use Cases

  • Fitness coaching
  • Weight management
  • Stress management
  • Sleep
  • Overall wellness
AI / ML-AS-A-SERVICE

White-Label AI Analytics For Digital Health

Our ML service makes it fast and easy to make scoring and predictions based on wearables data. Currently, we provide 3 white-labelled AI solutions.
White-Label AI Analytics For Digital Health

Scoring System

  • Sleep scoring, stress scoring
  • Wearables: Fitbit, Garmin, Whoop

Skin Analysis

  • Acne treatments, product recommendations, stress management & prediction
  • Phone camera, web camera

Voice Recognition

  • Snoring and unrest detection
  • Sensors: phone’s microphone
Use
cases:
  • Cheating detection

Cheating Prevention

Our an anti-cheating model prevents users from manipulating data in competitions or rewards programs. Our proprietary algorithm analyzes various data metrics to flag potential data manipulation and produces a binary output indicating whether a user has potentially over-inflated their steps count metric.

Cheating Prevention
Use
cases:
  • Sleep Scoring
  • Stress Scoring

Proprietary Scoring System

A unifying aspect of the majority of health-tech apps is that users need simple metrics at the front for a hassle-free path towards better health. With our wide variety of scoring systems you can customize a system of scores tailored for your use-case while saving on data and engineering teams’ work.

Track progress

Our scoring systems are all taylored for simple metric that can be tracked over time for progress evaluation.

Personalise

Most of our scores are made in a way that callibrates for your users based and personalize the experience.

Advice

Depending on your use-case and sale proposition, we build custom advice/system that helps having your users in the loop and engaged while they improve their health.
Use
cases:
  • Snoring detection
  • Unrest detection

Voice recognition

Snoring detection. We provide a quick way for you to integrate audio transformation for related problem analysis. Enlarge your users’ health feature store by adding additional sleep quality metrics like snoring and unrest during the sleep.

Voice recognition Spike

Our ML engineering team will ensure the white-labelled tool is calibrated to your use case during the implementation

Spike