AI systems for healthcare.
The workflow pattern we see in this industry, and what we would build for it.
01
Patient arrives
Intake forms, insurance checks, and consents are collected by hand at the front desk. The queue backs up.
02
Visit documented
The clinician types the note into the EHR, often after hours. Coding happens later, from memory.
03
Prior auth assembled
Staff pull clinical notes into a packet by hand and submit it to the payer portal. Then they wait.
04
Denial worked
Denied claims come back weeks later. Appeals are drafted one at a time from the chart.
A prior-auth and documentation agent.
An agent that drafts prior-auth packets from the clinical record, prepares visit documentation for clinician sign-off, and flags claims likely to deny before submission. Built with HIPAA controls and a full audit trail. Clinicians keep the final say on every note and every submission. The agent removes the after-hours paperwork.
10 to 14 weeks from kickoff to a live production system. We stay through adoption.
Daily output check
Checks what the system produced every day, beyond whether it ran.
Run tracing
Every run traced step by step, with each model call recorded.
Live production system
The working system in your stack, not a report.
Adoption Mile
To the 70 percent weekly-active bar by day 90.
Clinician time spent on EHR documentation
30 to 40 percent
IllustrativeFront-desk time on intake and verification
40 to 60 percent
IllustrativeDenial rate reduction from pre-submission checks
Varies by payer mix
Illustrative
Ranges are industry observations for orientation. They are not ClearForge results. Our results live on the proof page.
See the proofStart where every engagement starts. The fixed-fee Diagnostic maps this workflow in your clinic in 2 weeks.
Starting point · Forge Diagnostic