Build and manage predictive clinical models for integration into Epic

Epic is a healthcare software company which holds medical records of almost 54% of US patients

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About the Customer:

Healthcare Provider ($5B+ market cap)

Consistently ranked under top 15 providers in the US

In North America with over 45 hospitals and >2+ million patients

What is their starting point / ecosystem / tech stack ?

  • Azure
  • Epic
  • Interface Engine
  • Python
  • R

Predera Benefit

  • One stop platform for building, deploying and managing AI models
  • Continuous Improvement based on feedback from data scientists, experts and clinical staff
  • Business stakeholders can overwrite the output from AI models even in production environment using a sophisticated rule engine


  • Easy to install and setup
  • Business stakeholders can teach AI for Fraud Engines in 8 hours
  • Able to migrate all existing ML models and rules in less than a week
  • Integrated with data stores on AWS/ GCP - no extra support needed from IT/ data teams
  • Didn’t need to re-write workflow integration as it directly integrates with Slack and Hipchat for feedback from Customer support
  • Dedicated expert level support for onboarding

Business Impact

  • Business stakeholder -> fraud analysts -> customer support representatives  loop was tightened, reducing the feedback time by  80%
  • Saved 280 hours of stakeholder productivity per year
  • Reduced time to resolution of Fraud by 75% from ~20 mins to ~5 mins
  • Handle more fraud queues and volume with less people


“We would need two full-time data scientists with knowledge of marketing and acquisition campaigns for 6 months just to build out our Fraud Engine capability let alone the rest of monitoring and continuous automatic improvement provided by Predera. We could spend $300,000 to do that, or just buy Predera and have a mature Fraud and AI / ROI management platform today”