Meet our AI, Daniel

Your system for turning denied claims into collected revenue.

The reality is simple. Teams cannot keep up with the volume of denials.

So most of them sit untouched.

Daniel removes that limit.

It finds what went wrong. Applies the right fix. Sends the claim back out.

Powered by machine learning and healthcare trained GenAI, Daniel turns missed revenue into recovered revenue automatically.

Identify

We analyze denied claim lines across payers, policies, and coding patterns to surface high-confidence opportunities for recovery.

Remediate

Each denial is evaluated and corrected using structured, payer-specific logic to maximize the likelihood of approval.

Recover

Corrected claims are returned for payment at scale, ensuring every viable denial is processed without manual constraint.

Daniel The What

Daniel is our AI platform that uses advanced AI algorithms to automatically identify reasons for denials and how to solve them

Daniel uses large denial datasets for proprietary algorithms to automatically make corrections to denied claims

Daniel delivers automated claims submission to send corrected claims through the system to optimize revenue recovery

Daniel The How

Flowchart illustrating a process from claim submission to payment received, including steps: claim submission, denial detected, error analysis, fix applied, resubmission, and payment received, with a section indicating a contested claim for $12,850 and a continuous improvement feedback loop.

Data Science Flow

Daniel Results

100% of all denials are analyzed and processed

Graph showing upward trend with rising red arrow

Greater revenue from denials remediation

Target with an arrow hitting the bullseye

Increased accuracy of scoring system

Clock with a quarter-hour red segment and three black-hour markers

Less time required by billing staff

Calendar with a dollar sign symbol over it.

More timely and accurate accounts receivable

See how much revenue you are leaving behind.

Get a Denials Analysis
Get a Denials Analysis