AI Medical Coding Software | Reduce Claim Denials by 40%

AI-Powered Custom Medical Coding Software Built for Accuracy, Compliance & Speed

Purpose-built AI medical coding capabilities that automate code assignment and deliver up to 98% accuracy, 40% fewer denials, and 30% higher coder productivity.

Embedded Coding
Suggestions

Claims Auto-Population

Audit & Compliance
Alerts

Adaptive AI Learning
& Optimization

Embedded Coding Suggestions

Real-Time Intelligent Coding Assistance.

Embedded Coding Suggestions

Real-Time Intelligent Coding Assistance.

AI analyzes clinical documentation as it’s created and surfaces accurate ICD-10-CM codes in real time, reducing retrospective coding effort and improving diagnosis specificity at the point of care.

Automatically recommends appropriate CPT and HCPCS procedure codes based on documented services, minimizing missed charges and ensuring complete, compliant reimbursement for outpatient and specialty encounters.

Intelligently suggests correct modifiers based on clinical context and payer rules, reducing claim rejections caused by improper bundling, incomplete documentation, or incorrect procedural reporting.

Validates selected codes against clinical documentation and payer-specific rules to ensure medical necessity, proper sequencing, and regulatory alignment before claims are submitted.

Detects incomplete or insufficient documentation in real time and prompts providers or coders to add required details, reducing audit risk and preventing denials due to documentation gaps.

Claims Auto-Population

Automated, Submission-Ready Claims Generation.

Claims Auto-Population

Automated, Submission-Ready Claims Generation.

Automatically populates CMS-1500 and UB-04 claim forms with validated coding, provider, and patient data, reducing manual data entry errors and accelerating claims submission timelines.

Uses AI-driven mapping to convert structured and unstructured clinical documentation into billing-ready claim elements, ensuring accurate alignment between services rendered and reported charges.

Identify billable services directly from clinical notes and encounter data, minimizing missed revenue opportunities while ensuring complete and compliant charge capture across specialties.

Synchronizes patient demographics and insurance eligibility data from integrated EHR and practice management systems to reduce rework caused by outdated or mismatched payer information.

Performs automated validation checks before submission to identify missing fields, documentation gaps, or coding inconsistencies, helping reduce preventable denials and first-pass rejections.

Audit & Compliance Alerts

Proactive Audit & Compliance Monitoring.

Audit and Compliance Alerts Feature Image

Audit & Compliance Alerts

Proactive Audit & Compliance Monitoring.

Automatically detects National Correct Coding Initiative (NCCI) edit conflicts before claim submission, preventing improper code pairings and reducing rejections caused by bundling violations or coding inconsistencies.

Validates codes against Local and National Coverage Determinations to ensure medical necessity requirements are met, reducing payer denials due to non-covered or unsupported services.

Analyzes documentation depth and code selection patterns to flag potential upcoding or downcoding risks, helping maintain compliance and minimize audit exposure.

Ensures documentation supports MIPS measures and HCC risk adjustment coding, improving quality reporting performance and safeguarding revenue tied to value-based reimbursement models.

Generates real-time compliance scores for each encounter, providing visibility into documentation strength, coding integrity, and potential audit vulnerabilities before submission.

Adaptive AI Learning & Optimization

Adaptive AI Learning & Performance Optimization.

Revenue Optimization Analytics Feature Image

Adaptive AI Learning & Optimization

Adaptive AI Learning & Performance Optimization.

Learns from coder feedback, corrections, and historical claim outcomes to continuously improve coding accuracy, contextual understanding, and specialty-specific performance over time.

Customizes AI models for specialties such as cardiology, orthopedics, oncology, and primary care to ensure accurate code recommendations aligned with specialty documentation patterns.

Analyzes historical denial data to identify recurring coding issues, payer-specific trends, and documentation gaps—proactively reducing repeat denials and revenue leakage.

Dynamically adapts to payer-specific policies, coverage updates, and reimbursement rules, ensuring coding recommendations align with evolving requirements and minimize claim rework.

Provides real-time visibility into coding accuracy, denial rates, productivity improvements, and compliance scores—helping leadership track measurable ROI from AI implementation.

WHO IT’S FOR & WHAT IT SOLVES

AI Medical Coding Assistant for Healthcare Organizations Managing Complex Revenue Cycles

Designed for hospitals, RCM firms, and specialty practices focused on minimizing coding errors, clearing backlogs, and maximizing first-pass claim approvals.

Hospitals & Health Systems

High-volume inpatient and outpatient environments managing complex DRG, ICD-10, and CPT coding requirements. Reduce denial risk, eliminate coding backlogs, and strengthen compliance across enterprise revenue cycles.

Revenue Cycle Management Companies

Revenue cycle teams operating under tight SLAs and margin pressure. Improve coder productivity, reduce manual chart review, and increase first-pass claim acceptance with AI-driven coding automation.

Multi-Specialty & Large Medical Practices

Growing practices balancing clinical care with administrative burden. Automate charge capture, improve coding accuracy, and accelerate reimbursements without expanding internal coding teams.

Faster AI Adoption

Electronic Health Records (EHR)

Reduced Risk

Hospital Information Systems (HIS)

Scalable Infrastructure

Revenue Cycle Management (RCM)

Aligned AI Investments

Patient Management Systems (PMS)

Still Struggling with Frequent Claims Denial?

Get your free system assessment for AI medical coding software readiness.

CLIENTS TESTIMONIALS

Trusted by Healthcare Organizations Driving Measurable Revenue Improvements

See how data-driven strategies and intelligent systems translated into stronger margins and faster reimbursements.

"40% Reduction in Claim Denials Within 90 Days..."

Within the first quarter of implementation, we saw a measurable 40% reduction in coding-related denials. The AI recommendations significantly improved documentation specificity and DRG accuracy. Our coders now spend less time reviewing charts and more time resolving complex cases. The ROI was clear almost immediately.

Michael R. Bennett
Vice President of Revenue Cycle, Regional Health System

"Improved Coding Accuracy to 98% Across Specialties..."

The platform helped us standardize coding across multiple specialties and consistently maintain 98% accuracy. It reduced variability between coders and strengthened our compliance posture during audits. The real-time suggestions have been a game changer for our documentation workflows.

Jennifer L. Carter
Director of Health Information Management, Multi-Specialty Group

"30% Increase in Coder Productivity..."

Our coding team improved productivity by nearly 30% without increasing headcount. The automation of ICD-10 and CPT assignment eliminated repetitive manual tasks and reduced review cycles. It allowed us to scale operations while maintaining quality.

Daniel Whitman
Chief Operating Officer, National RCM Company

"Significant Improvement in First-Pass Claim Acceptance..."

We experienced a noticeable improvement in first-pass claim acceptance rates after implementing the AI medical coding assistant. Modifier accuracy and compliance checks dramatically reduced avoidable rejections. It strengthened both revenue performance and payer confidence.

Rachel M. Donovan
Revenue Integrity Manager, Community Hospital Network

"Stronger Audit Readiness & Compliance Confidence..."

The automated compliance alerts and documentation checks gave our team greater confidence during internal and external audits. Upcoding and downcoding risks are now proactively identified before submission. This has significantly reduced compliance-related stress.

Thomas J. Gallagher
Director of Compliance & Risk Adjustment, Medicare Advantage Organization

"Faster Claims Processing Without Workflow Disruption..."

Implementation was seamless, and the AI integrated directly into our existing EHR workflow. Claims move faster from documentation to submission, and our teams adapted quickly. We’ve reduced turnaround times without disrupting clinical operations.

Emily K. Sanders
Revenue Cycle Director, Urban Medical Practice Group

WHY THINKITIVE?

Empowering Healthcare Technology Innovation

250+

Healthcare Projects

400+

Healthcare Experts

98%

Client Retention Rate

150+

Healthcare Customers

50%

Cost Saving on Development

Revive Your Revenue Performance with Medical Coding AI

Thinkitive can help you build the best AI coding assistant that improves your financial health.

Frequently Asked Questions

Get answers to all your questions

Still have questions ?

Our AI medical coding assistant operates in a human-in-the-loop model, generating ICD-10, CPT, and HCPCS recommendations for coder review rather than submitting claims autonomously by default. This ensures compliance, transparency, and final validation before submission. Organizations can configure the system as a decision-support tool or a higher-level automated medical coding software solution based on internal governance policies. Confidence scores and documentation references support every suggestion.

Our AI medical coding software uses advanced clinical NLP to analyze operative notes and multi-specialty documentation. It understands procedural hierarchies, modifier requirements, bundling rules, and payer-specific guidelines. For complex cases, the system highlights primary and secondary procedures, suggests appropriate modifiers, and flags potential conflicts before submission—reducing errors in high-risk surgical encounters.

Yes. The AI medical coding assistant analyzes documentation for completeness and specificity. If required details are missing to justify a selected ICD-10 or CPT code, it generates real-time alerts for providers or coders. By prompting clarification before submission, this medical coding automation tool strengthens medical necessity validation and improves first-pass acceptance rates.

The platform compares documentation depth with selected codes to flag potential overcoding or undercoding patterns before submission. It assigns compliance confidence indicators and highlights inconsistencies. Using payer policies and rule engines, this AI for medical coding solution reduces audit exposure while maintaining human oversight for final approval.

Yes. The system supports HCC and risk adjustment workflows by identifying chronic conditions and documentation gaps tied to RAF scoring. Our AI medical coding software highlights suspected but undocumented conditions and recapture opportunities, improving value-based reimbursement accuracy while maintaining compliance standards.

By automating ICD-10 and CPT assignment, the automated medical coding software reduces manual review time and accelerates claim submission. Faster coding turnaround helps reduce Days in AR and Discharged Not Final Billed (DNFB) backlogs. Pre-submission validation checks minimize rework cycles, improving overall revenue cycle efficiency.

Yes. The platform includes built-in NCCI edit detection to identify improper code pairings and bundling violations before submission. This medical coding automation software validates code combinations against CMS guidelines and payer policies, reducing preventable rejections and compliance exposure.

The system uses adaptive machine learning to analyze corrections made by human coders. Over time, it refines recommendation accuracy based on specialty-specific documentation patterns and organizational preferences. This continuous learning loop ensures the AI medical coding software becomes more precise while maintaining governance control.

Yes. Every recommendation includes a traceable audit trail with supporting documentation references, rule validations, timestamps, and user actions. This transparency ensures compliance with internal audits and payer reviews, making the AI medical coding assistant suitable for enterprise health systems.

Yes. The system uses NLP and OCR technologies to extract structured insights from PDFs, scanned documents, operative reports, and handwritten notes. This enables the AI medical coding software to convert unstructured clinical documentation into accurate coding recommendations without manual data re-entry.