The future of AI-enabled intelligent revenue management.

Best-practice revenue cycle leaders use healthcare's most advanced AI-Enabled Financial Performance Tools to improve margin, accelerate cash and optimize staff performance.

in numbers

Providers see results with Etyon's data, insights and workflow automation tools.


Healthcare Organizations


Years of Healthcare Expertise


Data Points Analyzed


ROI Driven to Date


Revenue Cycle Leakage Stops Here.

Etyon's AI-enabled Financial Performance tools help leaders enhance insights and automation practices in some of the following areas:

Front-Office Denial Prediction

Predict denials prior to service to optimize front-end workflows and increase first pass payment rates.

Accounts Receivable Prioritization

Risk score every clean or denied claim in your accounts receivable every night to ensure appropriate aging policies and resource allocations across work-queues.

Staff Productivity / Touch Optimization

Know exactly how many touches and what cost resources are having on buckets or invoices to ensure optimal follow-up performance.

Order and Referral
Leakage Mining

Automatically find and quantify all order mismatch and missing referral leakage across physicians, services lines and more.

Payment Accuracy and Scorecarding

Determine payment accuracy on mixes of claims, payers, services and denials to ensure accurate and timely reimbursement.

Leakage Mining

Automatically find and quantify all registration leakage across locations, representatives and payer plans.

Automated Authorization
Status Review

Automatically audit the authorization request and delivery process to ensure all claims have appropriate authorizations prior to service.

POS Patient
Estimate Accuracy

Capture more cash and financially clear more patients prior to billing.

Leakage Mining

Automatically find and quantify dollars lost through non-covered services and claims management inefficiencies.

Vendor Placement
Recovery Audit

Automatically reconcile and audit claims placed with Vendors to ensure maximum external recovery efforts.

Treasury Reserve

Automatically determine reimbursement and recovery risk to determine accurate and consistent financial reserves.

ED Throughput

Identify optimal discharge times, schedule staff according to acuity, and understand ordering turnaround times.

Start simple, scale to sophistication

Leading the Way to AI-Enabled Revenue Cycle

Drive your revenue cycle to be more dynamic, collaborative, and intelligent with connected data, people and processes.

Data Chaining

Surface valuable insights when you collect, store, and clean your data.

Read more
AI and MLE

Automatically find answers in your data without the need for manual analysis.

Read more

Analytics-as-a-service (AaaS) automates 75% of data insights work.

Read more
Smart Workflows

Smarter decision support directly in your Electronic Medical Record.

Read more

Information is Everything.

Why You Should Start with Machine Learning, not RPA
In recent years, healthcare providers have increasingly been turning to automation technologies to streamline their revenue cycle management processes. Two popular options for this are machine learning-based data analysis and robotic process automation (RPA). While both approaches can be effective, there are compelling reasons to consider starting with machine learning-based data analysis.
Read More
Utilizing Data Analytics to Optimize Medical Coding Accuracy and Maximize Reimbursements
As the healthcare industry continues to evolve, healthcare providers are increasingly looking for ways to optimize their medical coding practices to ensure maximum reimbursement and compliance with regulatory requirements. One effective way to achieve this is through the use of data analytics, which can help healthcare providers identify trends and patterns in medical coding practices, leading to improved accuracy, better financial outcomes, and improved patient care.
Read More
Reducing Denial Rates through Data-Driven RCM
In the healthcare industry, revenue cycle management (RCM) is crucial for the financial success of healthcare organizations. One of the major challenges faced by healthcare providers is the high rate of claim denials. Denial rates can have a significant impact on the revenue cycle and the financial stability of healthcare organizations. However, with the implementation of data-driven RCM strategies, providers can identify the root causes of claim denials and reduce their denial rates.
Read More
What AI and ML in RCM Really Means
The healthcare industry is rapidly evolving, and the introduction of artificial intelligence (AI) and machine learning (ML) technologies is revolutionizing healthcare revenue cycle management (RCM). AI and ML are emerging as powerful tools that can improve healthcare operations and enhance patient outcomes. In this article, we will explore what AI and ML mean in healthcare revenue cycle management.
Read More
How Can I Improve How I Use My RCM Data?
As the healthcare industry becomes increasingly digitized, data has become an essential component of revenue cycle management. Efficient use of data can lead to better financial outcomes for healthcare providers, but it requires a deliberate and systematic approach. In this article, we will discuss several ways you can improve how you use data in healthcare revenue cycle management.
Read More
The Do’s and Don’t’s of Vendor Consolidation
Healthcare revenue cycle management (RCM) is a complex and multi-layered process that involves managing claims, billing, collections, and payments. As healthcare organizations continue to face financial pressures and operational challenges, vendor consolidation has become a popular strategy to streamline RCM processes, reduce costs, and improve performance. However, consolidating vendors is not a simple process, and it requires careful planning, implementation, and management to avoid potential pitfalls. In this article, we will explore the do’s and don’ts of vendor consolidation in healthcare RCM.
Read More
What are the 3 Layers of Denial Analytics?
Healthcare revenue cycle management is a complex process that involves multiple stages, from patient registration to payment collection. Denial management is a crucial aspect of this process, as it helps healthcare providers identify and address the reasons why claims are denied by insurance companies.
Read More
Are Analytic Platform Services a Thing of the Past?
Analytics platform services have been a cornerstone of businesses' efforts to make sense of their data and gain insights into their operations. However, with the rise of machine learning and artificial intelligence, some have questioned whether analytics platform services are becoming a thing of the past. In this article, we will explore whether analytics platform services are still relevant and necessary in today's data-driven world.
Read More
What Does RPA Even Really Mean?
In recent years, RPA has become an increasingly popular buzzword in the business world. Many companies are turning to RPA to streamline their operations, reduce costs, and improve efficiency. But what does RPA even really mean? In this article, we will explore the basics of RPA and how it is being used in today's business landscape.
Read More
Partners say

Don’t take our word for it - hear from your provider peers

"We're now working the right accounts at the right times to where our timely filing write-offs reduction have drastically reduced and that's great."


"When you combine amazing technology with folks that know revenue cycle challenges inside and out, you get tremendous results."

Lab Director

" I knew we had denial challenges, but could never uncover them as quickly as Etyon's solutions allows us to without all the effort."

Director Process Improvement

AI-Enabled financial performance tools

Still curious? Start your free month today.