medicalbiller.ai
A new operating model for medical billing
The first AI-native medical billing company.
An autonomous revenue cycle, supervised by experts. Prepared for physicians and practice leaders.
Abstract
Medical billing remains a labor business in a software costume. Denials are reworked by hand at twenty five to fifty seven dollars each, and eligibility is verified by people on hold. Not billing software you bolt onto a team. The billing operation itself, rebuilt AI-first, where autonomous agents work every claim from the first call to the final dollar. The result is a revenue cycle that classifies, calls, scrubs, submits, posts, appeals, and reconciles on its own, with a human approving every consequential step.
Key results
The denial problem is not mysterious. Industry data attributes most denials to registration errors, missing authorization, and coding mistakes, all repetitive, rule bound work.1 It is precisely the kind of work that machines perform well.
The incumbent response has been to add people, often offshore, to the phones and the rework queues. That is labor arbitrage, and arbitrage erodes. The alternative is to rebuild the operation so that agents do the calling, the classification, and the posting, natively.2
1. Denial root causes, industry distribution. 2. Venture funding into AI revenue cycle grew roughly 340 percent year over year, 2024 to 2026.
Agents that call your payers
Autonomous voice agents dial insurance companies, navigate phone trees, sit on hold, and converse with reps to verify coverage, then hand you back clean structured data.
<$0.50 per verification call, vs $5 to $15 manual
- +Verifies eligibility, benefits, copay, coinsurance, deductible and out-of-pocket status
- +Captures prior authorization requirements and in or out of network status
- +Navigates the largest national payer phone systems automatically
- +Up to 1,000 concurrent calls, run in batches around the clock
- +Every call recorded, transcribed, and extracted to structured fields
- +Medical-tuned speech recognition for clinical and insurance terminology
Denials, overturned by machine
Drop in a denied claim in any format. It is classified against a five million row knowledge base, the appeal deadline is calculated, and an edit-ready appeal letter is drafted with cited evidence.
~90s to assess a denial and draft the appeal, vs 20 to 30 min
- +Accepts structured API, free text, spreadsheet exports, remittance files, or a form
- +Six-category denial framework with real-denial-versus-adjustment detection
- +Deadline math with receipt-presumption, payer and state filing windows
- +Appeal letters cite the exact reason code, payer rule, or coverage policy
- +Expected success probability per denial, so teams work the winnable ones first
- +Routes to the correct channel: portal, mail, fax, or peer-to-peer
One platform, the whole cycle
The system of record for everything. Charge capture, clean-claim scrubbing, clearinghouse submission, automatic payment posting, accounts receivable, collections, credentialing, and reporting.
80+ scrub rules that prevent denials at the source
- +More than 80 pre-submission scrub rules catch denials before they happen
- +Electronic 837 submission with status polling and full error logging
- +Automatic remittance posting that matches payments and applies write-offs
- +Direct EHR integration and clearinghouse connectivity
- +AR aging, collections, statements, payment plans, and deductible tracking
- +More than 40 report types and real-time financial dashboards
Each claim is processed in seven stages. An agent performs the work at every stage; a human reviews before anything is filed or paid.
Capture
Intake agentCharge and clinical intake, coded per visit
Verify
Voice agentVoice agent calls the payer and confirms coverage
Scrub
Scrub agent80+ rules check the claim before it leaves
Submit
Submit agentElectronic 837 to the clearinghouse
Post
Posting agentRemittance matched and posted automatically
Appeal
Denial agentDenials classified and appealed in ~90 seconds
Settle
AR agentPaid, reconciled, and reported
| Reference set | Records |
|---|---|
| Procedure-to-procedure bundling edit pairs | 4,493,738 |
| Diagnosis codes | 74,719 |
| Procedure and supply codes | 9,068 |
| Remittance advice remark codes | 1,198 |
| Claim adjustment reason codes, denial-tagged | 308 |
| Local coverage determinations | 949 |
| National coverage determinations | 357 |
| Medicare fee schedule entries | 19,000+ |
| Measure | Value | Basis |
|---|---|---|
| Cost per autonomous verification call | <$0.50 | verified |
| Reduction in manual calling effort | ~90% | verified |
| Target cost per denial reworked, vs $25 to $57 industry | <$5 | target |
| To classify a denial and draft an appeal | ~90s | verified |
| Rows in the clinical and regulatory knowledge base | 5M+ | verified |
| Concurrent payer calls at peak | 1,000 | verified |
| Pre-submission scrub rules | 80+ | verified |
| Report types and live dashboards | 40+ | verified |
Deterministic before generative
Codes, coverage policies, and deadline math come from exact database lookups. The AI judges and writes. It does not invent the facts, so it cannot hallucinate a code or a deadline.
A human on every consequential move
Agents draft appeals and surface recommendations. A person approves before anything is filed. Autonomy with a hand on the wheel.
Every action is auditable
Each classification, call, and posted payment records the evidence and the model that ran it, so any decision can be reviewed end to end.
Built for protected health information
Encryption in transit and at rest, role-based access, and activity logging throughout. Claim identity stays operator-controlled.
| The old way | medicalbiller.ai |
|---|---|
| Offshore callers on hold all day | Voice agents call payers, 1,000 at once |
| Denials reworked by hand, one at a time | Denials classified and appealed in ~90 seconds |
| Software bolted onto a manual team | Agents are the operation, not an add-on |
| You manage the people | You watch the dashboard |
Is AI safe for claims and protected health information?
Yes. The facts come from the knowledge base by exact lookup, the AI only judges and drafts, every action is logged, and a human approves anything that gets filed. Encryption and role-based access run throughout.
Will it hallucinate codes or deadlines?
No. Codes, coverage policies, and deadline math are exact database lookups, not model guesses. It is not the model's job to know the codes, it is the database's job.
Do I have to replace my current systems?
No. The platform is the system of record and it connects to the clearinghouse and EHR you already use. We meet your data where it lives: API, spreadsheet export, remittance file, or direct integration.
Is this just an offshore team with a chatbot?
No. This is software doing the work, supervised by a small expert team. Not a large team holding a tool.