$14.1B
$14.1 Billion in Improper Medicare Payments Last Year. The Root Cause: Coding and Documentation Errors That AI Catches Before Submission.
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Six Core Capabilities of the AI Medical Coding Agent
From clinical NLP analysis and ICD-10/CPT/DRG assignment to NCCI validation, CC/MCC capture, and revenue integrity auditing.
Clinical NLP & Code Extraction
Clinical NLP extracts diagnoses and procedures from notes at 96.7%+ accuracy.
DRG Optimisation & CC/MCC Capture
MS-DRG and APR-DRG engine lands the accurate DRG via Medicare grouper logic.
NCCI Validation & Edit Management
Real-time NCCI PTP checks catch bundling conflicts before claims.
Coding Queries & CDI Integration
AHIMA/ACDIS-compliant, non-leading physician queries when docs need attestation.
Revenue Integrity & Compliance
Pre-submission audit screens claims against OIG, RAC, and MAC LCD risk targets.
Coding Performance & Analytics
Real-time dashboard tracks time-to-code, first-pass rate, and CC/MCC capture.
$14.1 Billion in Improper Medicare Payments Last Year.
The same documentation gaps that prevent accurate DRG assignment also create audit risk when RAC contractors review the claim.
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The $14 Billion Coding Error Crisis Draining Every Specialty's Revenue
Every number comes from production revenue-cycle deployments — measured live, not projected in a pitch deck.
94%
first-pass claim acceptance rate achieved when AI medical coding replaces manual coding workflows — up from the 71% industry baseline — translating…
100+
Enterprise customers trusting Bonami X AI for mission-critical healthcare and revenue cycle operations.
24/7
Autonomous monitoring with real-time alerts — continuous automated intervention across every workflow.
Our Process
Why Choose the AI Medical Coding Agent
Drag, click, or use the dots to walk through each reason.
Coding Specificity at Scale — Not Just Coding Speed
A 5% MCC capture-rate gain across 15,000 inpatient discharges recovers $6.4M a year — specificity the clinical record already supports.
Compliance Confidence Before the Claim Leaves the Building
The AI agent validates every claim against current OIG Work Plan priorities and MAC LCDs before submission — not after the audit.
Coders as Clinical Coding Experts — Not Data Entry Operators
With AHIMA projecting a 20–30% coder shortfall by 2027, the agent handles extraction and validation so coders focus on clinical judgment.
Works With Your EHR, Coding Platform, and Billing System
The AI Medical Coding Agent connects to leading EHR, computer-assisted coding, and clearinghouse platforms.
Epic
Epic EHR integration for inpatient and outpatient medical coding
Oracle Health
Oracle Health Cerner integration for ICD-10 and DRG coding
Availity
Availity integration for pre-submission claim code validation
athenahealth
athenahealth integration for ambulatory CPT and ICD-10 coding
eClaimLink
eClaimLink UAE integration for DHA and HAAD medical coding
Daman
Daman UAE integration for clinical coding compliance
From the Desk of Our Esteemed Clients
Real results from enterprises that have deployed Bonami's AI solutions across industries.
Bonami's AI platform revolutionized our content creation process. Their natural language generation tools helped us scale our content production by 300% while maintaining exceptional quality and brand voice.
Stop Leaving Clinical Complexity Uncoded and Unreimbursed
Every missed CC/MCC, every unspecified ICD-10 code, every NCCI edit that generates a denial — revenue that existed in the clinical record, lost to a documentation-to-code translation failure.
Book Coding Accuracy Demo
Six Core Capabilities of the AI Medical Coding Agent
From clinical NLP analysis and ICD-10/CPT/DRG assignment to NCCI validation, CC/MCC capture, and revenue integrity auditing.
01
Clinical NLP
Clinical NLP extracts diagnoses and procedures from notes at 96.7%+ accuracy.
02
DRG Optimisation
MS-DRG and APR-DRG engine lands the accurate DRG via Medicare grouper logic.
03
NCCI Validation
Real-time NCCI PTP checks catch bundling conflicts before claims.
04
Coding Queries
AHIMA/ACDIS-compliant, non-leading physician queries when docs need attestation.
05
Revenue Integrity
Pre-submission audit screens claims against OIG, RAC, and MAC LCD risk targets.
06
Coding Performance
Real-time dashboard tracks time-to-code, first-pass rate, and CC/MCC capture.
Get in touch
Ready to Recover the Revenue Your Clinical Complexity Has Already Earned?
Get a live Medical Coding Agent demo on your encounter volume, plus a coding accuracy assessment of CC/MCC capture and NCCI risk.
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Frequently Asked Questions
[ 1 ]
What is an AI Medical Coding Agent and which code sets does it handle?
An AI Medical Coding Agent reads EHR documentation, extracts diagnoses and procedures via clinical NLP, assigns codes, validates against compliance rules, and presents the result for coder review with a full audit trail.
[ 2 ]
How does the NLP model handle ambiguous or poorly structured clinical documentation?
The NLP is trained on real clinical documentation across specialties and EHR formats, not a general model applied to medical text. It understands negation, uncertainty, and temporal context — "rule out sepsis" generates no sepsis code.
[ 3 ]
What is the first-pass claim acceptance rate and how is it measured?
First-pass claim acceptance rate (FPAR) is the share of claims paid on first submission without denial or rework. The manual baseline is 71% FPAR (MGMA/Advisory Board); Bonami deployments achieve 94%+, measured via clearinghouse clean claim rate and payer EOBs.
[ 4 ]
How does the agent handle DRG optimisation without creating upcoding risk?
DRG optimisation is not upcoding. Upcoding assigns codes documentation does not support; optimisation captures every CC and MCC genuinely documented so DRG assignment reflects actual complexity.
[ 5 ]
How does the physician query process work, and does it comply with AHIMA guidelines?
Yes. Queries comply with the AHIMA and ACDIS 2019 joint guidelines: non-leading, citing specific clinical evidence, and offering multiple response choices including "clinically undetermined".
[ 6 ]
Which EHR systems and coding platforms does the agent integrate with?
EHR integration via FHIR R4 and HL7 v2 covers Epic (incl. SMART on FHIR), Oracle Health/Cerner, athenahealth, NextGen, and eClinicalWorks — it enhances existing CAC environments rather than replacing them.
[ 7 ]
How does the agent handle specialty-specific coding requirements?
Coding requirements differ materially by specialty in code sets, documentation patterns, and payer policy. The agent deploys NLP models calibrated per specialty: inpatient medicine and surgery for discharge summaries, oncology for cancer
[ 8 ]
How long does implementation take and what ROI timeline should we expect?
A focused deployment (one EHR, top five payers, top 10 DRGs) runs 10–14 weeks: FHIR setup and NLP calibration, then shadow mode, a controlled pilot, and phased expansion.
[ 9 ]
How is computer assisted coding software different from this medical coding software?
Traditional computer assisted coding software suggests codes and leaves full assignment and validation to the coder. Bonami's AI medical coding software codes end to end: it reads documentation, assigns the complete ICD-10 and CPT code
[ 10 ]
Does the automated medical coding handle both ICD-10 and CPT coding software requirements?
Yes. This purpose-built ICD-10 and CPT coding software assigns ICD-10-CM diagnosis codes for all care settings, ICD-10-PCS inpatient procedure codes, and CPT/HCPCS codes for outpatient encounters.
[ 11 ]
Who builds and runs this agent?
This agent is one of 32 built and maintained by Bonami X AI, our production AI agent division. If you want an agent like this scoped for your own workflow, our AI agent development company team handles discovery, build, integration, and support end to end.
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