Prewave Case Study

Using advanced machine learning to predict real-time supply chain risk

 

Industry

Customer application

  • Real-time predictive risk alerts

NoSQL solution

Use case

  • Machine learning
  • Data store
  • Caching

Product

Key features

Prewave white

Prewave is a data analytics startup committed to making worldwide supply chains more transparent, resilient, and sustainable. Their AI technology analyzes social media and news media data in over 50 languages and uses advanced machine learning to deliver predictions on critical risks to their customers’ supply chains. Prewave chose Couchbase as their main operational data store and cache for its ability to seamlessly stream thousands of media messages daily, reduce query time from minutes to seconds, and dynamically scale to complement their product’s evolution.

“Couchbase is easy to use, quick to set up, and simple to scale. It is the Swiss pocket knife of NoSQL databases.”

Harald Nitschinger
Co-Founder & Managing Director, Prewave

CHALLENGES

  • Needed a flexible and dynamic query capability

  • Required high-performance cache for their operational data store

  • Wanted a scalable, dynamic, and future-proof solution to enable cost-effective product evolution

OUTCOMES

  • Thousands of streaming queries during every 24-hour analysis period

  • Data loads and queries reduced from minutes to seconds

  • From proof of concept to production within two months