Automated Clinical Coding
Read pathology and lab reports, identify procedures and diagnoses, and assign CPT and ICD-10 codes with evidence-based confidence.
MIXI AI turns clinical reports into clean, compliant claims in seconds. Read reports, assign CPT and ICD-10 codes, validate payer rules, and learn from real denial outcomes to maximize reimbursement.
From the moment a clinical report is finalized to the moment payment posts, MIXI AI handles coding, claim generation, denial prevention, payer learning, and reimbursement optimization.
Read pathology and lab reports, identify procedures and diagnoses, and assign CPT and ICD-10 codes with evidence-based confidence.
Transform coded reports into submission-ready claims with modifiers, units, diagnosis pointers, and payer-specific formatting already in place.
Cross-check every claim against compliance rules, historical denial patterns, and payer requirements before submission.
Ingest payment and denial responses automatically to understand what pays faster, what gets rejected, and why.
Build an organization-specific knowledge base from real claims, real payers, and real reimbursement outcomes.
Catch under-coding, missed add-on codes, and documentation gaps using historical payer acceptance profiles and billing intelligence.
Each step is validated, auditable, and continuously improved by learning from your historical outcomes.
Receive clinical reports through PDF, text, HL7, or integration. MIXI AI extracts structured data from varied lab formats without templates.
The model reads the clinical narrative, identifies specimens and procedures, and assigns CPT and ICD-10 codes with evidence scoring.
Validate against NCCI edits, LCD policies, MUE limits, medical necessity links, modifier rules, and payer-specific logic.
Assemble clean claims with correct units, modifiers, diagnosis pointers, and submission formatting for clearinghouse routing.
Analyze 835 and ARA responses, map denial codes, and feed outcomes back into MIXI AI to improve future claims automatically.
Unlike static rule engines, MIXI AI builds a living knowledge base from real billing outcomes and adapts to the way your organization gets reimbursed.
Build payer-specific acceptance profiles showing exactly which code combinations get paid and which get denied.
Interpret coverage policies, frequency limits, prior authorization requirements, and organization-specific payer behavior.
Every payment, denial, and adjustment trains the platform further, steadily improving coding accuracy and reimbursement outcomes.
Learn from your specialty, payer mix, and coding history to deliver recommendations tailored to your practice.
Catch the issues that cause denials, audits, and revenue leakage before claims ever reach a human reviewer or payer.
Detect code pairs that should not be billed together under National Correct Coding Initiative rules.
Validate CPT and diagnosis combinations against local coverage determinations and MAC guidance.
Ensure units per CPT code do not exceed medically unlikely edit thresholds.
Verify that CPT-to-ICD linkages are supported by established clinical and reimbursement rationale.
Recommend appropriate modifiers such as TC, 26, and 59 based on service context and payer requirements.
Use historical payer outcomes to flag combinations with elevated denial probability before submission.
MIXI AI is designed for healthcare organizations of all sizes, from single-lab practices to multi-site enterprise operations.
Support for super admin, org admin, billing specialist, coder, and reviewer workflows with least-privilege access.
Keep each organization’s data, claim history, and learned intelligence logically separated and secure.
Automatically detect and redact sensitive data before it reaches the AI engine where required by policy.
Track coding decisions, reviewer actions, edits, and approvals with timestamps and user attribution.
See how MIXI AI can accelerate coding, reduce denials, and continuously improve reimbursement performance across your organization.