RevCaptureAi | ElectrifAi

START capturing missed revenue and improve compliance audit in weeks

Predict, identify, and capture missed charges, boost revenue cycle integrity, and improve compliance with the power of pre-built ML solutions

Capture missed revenues in weeks, predict, identify, and capture claims accurately in the first pass using the power of ML

Achieve revenue excellence through self-learning ML boosting revenue integrity over time with more data and user interaction

Improve compliance audit to evaluate the accuracy of operational, clinical, and documentation metrics, including coding

Easy to deploy on-premise or hosted as a service with support for leading EHR and EMR and no ongoing consulting or hidden costs

Enjoy results in 6-8 weeks with a low upfront cost followed by a gainshare model ensuring successful business outcomes

Realize 2-4% savings in 6-8 weeks rather than months and years

Value Proposition

With low upfront investment, shared success, and quick revenue capture, RevCaptureAi pays for itself through missed revenue recovery, improved compliance audit with no hidden fees

Flexible business models
‍Subscription or Gainshare

Save 2-4% in 6-8 Weeks
Rapid Time to Value

Zero spend on product consultants
‍Faster, better, cheaper

Disparate data sources, no problem
Structured, Unstructured to Scattered data

Responsible AI
Transparency and Explainability

End-to-end
We do the heavy lifting from ingestion to insights

Why is RevCaptureAi better?

With our Gainshare model, we live up to our words and offer to make our money only after we save for you. The critical tool in overcoming procurement challenges is leveraging your data with AI/ML. We have proven solutions that work for Fortune 5 to mid-sized enterprises across all industries

RevCaptureAi

ML based approach with self learning continues to get better with more user interaction and data
Ready to use pre-trained, fully operational
Stop revenue leakages in 6-8weeks

Rules-based IT solutions

Rule-based systems don’t learn. Need to keep rules updated, tested and deployed. Expensive and painful
Inability to look at data in multiple dimensions that machine learning can