# Arkangel AI (full content) Arkangel AI is a medical-first research and care copilot for clinicians, care teams, researchers, and healthcare organizations. Arkangel AI combines evidence-based medical search, citation-backed answers, clinical workflows, ICD-10 support, and long-running research automation in one platform. This file carries the expanded content of the pages indexed at https://arkangel.ai/llms.txt, so it can be read in a single request instead of crawling each page. Both files are generated from the same canonical page set and cannot drift apart. Each section below is labeled with the canonical URL it describes. Content is published in English unless a section states otherwise. ## Core product ### Home URL: https://arkangel.ai/ Review every chart before day’s end. AI reviews 100% of records, surfaces priority findings, and keeps every recommendation auditable. ### Pricing URL: https://arkangel.ai/pricing Every plan includes complete chart review capabilities. Start free and scale from solo practitioners to enterprise health systems. Full chart intelligence on every plan: start free, scale as you grow, and only pay for the value you capture. ### Machine-readable pricing URL: https://arkangel.ai/pricing.md Machine-readable pricing for Arkangel AI plans, served as markdown. These tiers mirror the public pricing page and carry each plan’s description, monthly and yearly price, billing period, and included features. ### FAQ URL: https://arkangel.ai/faq Find answers to common questions about Arkangel AI. ## Medical AI ### AI for doctors URL: https://arkangel.ai/ai-for-doctors AI-powered clinical assistant designed for doctors, medical professionals, and healthcare teams. Get instant evidence-based answers, improve diagnostic confidence, and streamline clinical decision-making. ### AI for medical coders URL: https://arkangel.ai/ai-for-coders AI-powered PDF conditions highlighter for clinical coders and billing specialists. Surface candidate ICD-10 conditions from medical records, highlight source text, and support reviewer validation. One upload, annotated PDF for reviewer validation. ### Medical audit URL: https://arkangel.ai/medical-audit Upload a medical record and medical order to draft a medical-necessity review, highlight supporting evidence, and help reviewers decide what is ready for prior authorization. ## Clinical solutions ### Clinical quality URL: https://arkangel.ai/clinical-quality Scale high-quality care delivery with AI chart review. Validate documentation to support quality measures, clinical decision support tools, and clinical standards. #### Why is clinical documentation quality so hard to scale? Quality depends on documentation, yet teams can only manually review a small share of charts. Missed diagnoses, care-gap omissions, and weak documentation slip through—hurting patient outcomes, lowering HEDIS/STARS scores, and exposing providers to audit risk. The gap widens as volume grows, because adding reviewers rarely keeps pace with chart counts. #### How does AI improve clinical quality at scale? AI reviews 100% of charts in real time against HEDIS/STARS measures, clinical decision support, or your own standards. It surfaces care gaps, builds provider scorecards, and sends automated feedback to clinicians. Because every chart is checked—not a sample—quality scores rise, documentation stays audit-ready, and improvement scales without expanding your review team. #### How do you roll out AI clinical-quality review? Rollout has three steps. An engineer configures the AI to your quality criteria and EHR. The platform then reviews every chart in real time, pulling directly from the record with reasoning and recommendations. Finally, it sends automated feedback to clinicians and aggregates dashboards—turning one-off audits into continuous, measurable quality improvement. #### Is AI quality review better than manual chart audits? Manual quality audits sample a fraction of charts, so care gaps and documentation errors go undetected until scores drop or an audit lands. AI reviews every chart in real time, flags gaps against your quality measures, and feeds findings straight to clinicians—lifting HEDIS/STARS performance without growing the review team. ### Outpatient coding URL: https://arkangel.ai/outpatient-coding Bill accurately and reduce preventable denials. Automated pre-bill CPT/ICD-10 coding audits catch errors before submission, helping teams submit cleaner claims and reduce compliance risk. #### What causes denials and lost revenue in outpatient coding? Outpatient denials and lost revenue come from three sources: undercoding that leaves earned reimbursement uncaptured, overcoding that triggers audits and repayment, and manual review that only covers 5–10% of charts. Because most charts are never audited before billing, errors reach the payer and surface as denials, delays, and compliance exposure. #### How does AI pre-bill coding review reduce denials? AI audits 100% of charts before submission, comparing each claim to documentation and payer rules. It catches undercoded services and missed add-on codes, flags overcoding and LCD/NCD mismatches, and routes corrections back to the EMR. Cleaner claims go out the first time, so denials drop and reimbursement becomes more predictable—without adding coders. #### How do you implement AI pre-bill coding audits? Implementation takes three steps. An engineer configures the AI to your coding requirements and payer rules. Every chart is then reviewed in real time before billing, catching errors and optimization opportunities. Finally, automated feedback flows back to your EMR, streamlining corrections and steadily improving documentation quality—typically live within four to six weeks. #### Is AI coding review better than manual audits? Manual coding audits review only 5–10% of charts, usually after billing, so undercoding and overcoding slip through and return as denials. AI audits 100% of charts before submission, applies current payer and LCD/NCD rules consistently, and pushes corrections to your EMR—cutting denials and capturing revenue without adding coding staff. ### Payer compliance URL: https://arkangel.ai/payer-compliance Be audit-ready on every claim. Ensure charts prove medical necessity and services before payer audits occur. Arkangel AI validates documentation to prevent denials and clawbacks. #### What triggers a payer audit in healthcare? Payer audits are usually triggered by billing outliers—high CPT volumes, duplicate claims, and peer-comparison flags—combined with documentation gaps like unsupported medical necessity or missing signatures. Prior-authorization and LCD/NCD violations add risk. Catching these issues before claims are submitted is the most reliable way to avoid costly clawbacks and repayments. #### How does AI chart review improve payer compliance? AI chart review reads every chart before billing and validates each service against payer policies, LCD/NCD rules, and documentation standards. It flags missing medical necessity, coding errors, and documentation gaps in real time, so teams fix them pre-submission. The result is fewer denials, fewer clawbacks, and consistent, audit-ready documentation across the organization. #### How do you set up AI payer-compliance review? Setup takes three steps. First, an engineer configures the AI to your payer contracts, LCD/NCD requirements, and compliance thresholds. Next, every chart is reviewed pre-bill in real time, surfacing documentation and medical-necessity gaps. Finally, the platform automates corrections and compiles audit-ready reports with full traceability—so compliance becomes continuous, not a periodic scramble. #### Is AI chart review better than manual auditing? Manual auditing samples a small fraction of charts after billing, so most errors slip through and surface only when a payer claws money back. AI reviews 100% of charts before submission, applies the same rules every time, and flags issues while they can still be fixed—cutting denials and audit exposure at a fraction of the cost. ### Payer compliance solution URL: https://arkangel.ai/solutions/payer-compliance Solution-page view of the payer compliance offering described at /payer-compliance: ensure charts prove medical necessity and services before payer audits occur, with AI-powered documentation review. ### Revenue discovery URL: https://arkangel.ai/revenue-discovery Turn compliance risk into revenue with AI-powered chart review. Capture every missed billable service with 100% pre-bill chart review. Arkangel AI identifies undercoding, missed add-on services, and preventable denials before claims submission. #### Why do providers leave revenue uncaptured? Providers lose roughly 11% of RVUs per patient to systematic underbilling. Conservative E/M levels, unbilled add-on services, and missed preventative or chronic-care work go uncaptured at every encounter. Up to 70% of denials are preventable too. Because manual review can't cover every chart, these gaps compound into substantial annual revenue loss. #### How does AI recover missed billable revenue? AI reviews 100% of charts before billing and compares documentation to payer rules. It surfaces undercoded visits, missed add-on services, and reimbursable preventative or chronic-care work, then confirms the documentation supports each code. Corrections flow back to the EMR—so you capture compliant, maximum reimbursement instead of leaving earned revenue on the table. #### How does AI revenue discovery work? It works in three steps. First, the AI is configured to your billing criteria, payer rules, and specialty requirements. Next, it reviews 100% of charts pulled from your EHR before submission, flagging revenue opportunities. Finally, corrections push back to your EMR or queue for approval, generating compliant claim files ready to submit. #### Does AI capture more revenue than manual coding? Manual coding reviews a small share of charts and tends toward conservative billing, so undercoded visits and missed add-on services stay unbilled. AI reviews every chart before submission, identifies each documented billable service, and verifies support for every code—recovering an average 11% of RVUs while keeping claims compliant and audit-ready. ### Risk adjustment URL: https://arkangel.ai/risk-adjustment Identify gaps in care, improve patient outcomes, and maximize revenue opportunities with AI-powered risk adjustment and HCC reviews. #### How do you prepare for a RADV audit? RADV audits validate that submitted diagnosis codes are supported by medical records. To prepare, AI reviews claims data against documentation, flags unsupported or missing codes, and routes exceptions to coders with prioritized action items. It then generates audit-ready summaries—so when CMS requests records, your HCC coding is already defensible and fully traceable. #### Why use AI for HCC risk-adjustment coding? AI reads 100% of charts instead of a small sample, surfacing conditions buried in notes, labs, and medication lists that manual review misses. Clinically trained models deliver high recall with evidence for every suggested code, integrate with 20+ EHRs, and track RAF impact—so you capture accurate risk scores without adding coder headcount. #### Does AI capture more HCCs than manual chart review? Manual HCC review samples a fraction of charts after billing, so documented conditions go uncoded and revenue is left on the table. AI reviews every chart before submission, links each suggested code to evidence, and flags unsupported codes—raising accurate RAF capture while keeping the documentation defensible if CMS audits. ### Medical coding local URL: https://arkangel.ai/medical-coding-local AI-powered medical coding, billing optimization, and revenue integrity support for physicians and healthcare organizations in New Braunfels, Texas. #### Is AI coding better than outsourcing for a small practice? Outsourced coding adds per-claim fees, slow turnaround, and little visibility, while manual in-house coding limits how many charts you can review. Arkangel AI automates ICD-10 and CPT coding on 100% of charts, flags denials and missed revenue before submission, and keeps the work in your control—accurate reimbursement without enterprise cost. ## Medical coding resources ### ICD-10 hub URL: https://arkangel.ai/icd-10 Search over 70,000 ICD-10 diagnosis codes in 4 languages. Free ICD-10-CM code lookup for medical coders, billers, and healthcare professionals, with specialty-specific code collections. #### What is ICD-10 and how do you find the right code? ICD-10-CM is the U.S. system for coding diagnoses, maintained by the CDC and NCHS, with over 70,000 codes across 21 chapters. To find the right code, search by diagnosis, symptom, or code—for example "diabetes" or "J18.9"—then confirm laterality, episode, and specificity. Accurate, specific codes drive correct documentation and reimbursement. #### Is AI-powered ICD-10 search faster than manual lookup? Manual ICD-10 lookup means paging through alphabetic indexes and tabular lists, then cross-checking laterality and specificity by hand—slow and error-prone. Arkangel AI search matches a diagnosis, symptom, or partial code against all 70,000+ codes in four languages instantly, surfacing the most specific match so coders confirm rather than hunt. ### ICD-10 basics URL: https://arkangel.ai/icd-10/basics Master the fundamentals of ICD-10 coding with our comprehensive guide covering everything from basic concepts to coding best practices. ### Common ICD-10 codes URL: https://arkangel.ai/icd-10/common-codes Browse common ICD-10 diagnosis codes organized by medical specialty. Find cardiology, neurology, orthopedics, pulmonology, pediatrics, and oncology codes. ### Calculators URL: https://arkangel.ai/calculators Free calculators to estimate revenue recovery, staffing savings, and clinical impact from healthcare AI. ### Audit calculator URL: https://arkangel.ai/audit-calculator Compare what your team can review today versus what AI-assisted review could cover. Results are estimates based on industry averages. Actual values may vary depending on case complexity, insurer type, and specific operational conditions of each organization. ### ICD-10 billing calculator URL: https://arkangel.ai/icd10-billing-calculator Estimate revenue you could recover by catching missed codes and billing errors before claims go out. Estimates assume a 50% recovery rate from coding optimization, over a coding loss rate that typically ranges from 1-5% according to HFMA references. ### AI savings health calculator URL: https://arkangel.ai/ai-savings-health-calculator Estimate yearly time and cost savings from automating repetitive clinical and administrative work. Assumes the company saves 2 business days per active full-time medical persona per month (24 per year). This calculator provides an estimated value and is not a guarantee of results. ## Research and education ### Medical documentation URL: https://arkangel.ai/docs API documentation and guides for Arkangel AI. ### Research URL: https://arkangel.ai/research Advanced research capabilities for comprehensive medical analysis and insights, published as a library of research articles. ### Resources URL: https://arkangel.ai/resources Educational resources and insights for healthcare professionals. ### University URL: https://arkangel.ai/resources/university Healthcare AI courses and educational programs from Arkangel AI University. ### Generative AI in Healthcare course URL: https://arkangel.ai/resources/university/course-generative-ai-in-healthcare Discover how to use large language models effectively in healthcare, from core concepts to practical applications with Arkangel AI. ### Introduction to Artificial Intelligence in Healthcare course URL: https://arkangel.ai/resources/university/course-introduction-to-artificial-intelligence-in-healthcare Learn the fundamentals of AI for clinical and operational use-cases with a practical, hands-on curriculum. ### Boston Scientific medical devices AI (podcast) URL: https://arkangel.ai/resources/podcast/boston-scientific-medical-devices-ai Discover how Boston Scientific is integrating AI into their medical devices. Laura Velásquez from Arkangel AI speaks with Boston Scientific representatives about integrating AI in medical devices. Intelligent medical devices are redefining clinical procedures and improving patient outcomes. Published 2025-08-01 by Jose Zea. ### AI and ICD-10 coding accuracy URL: https://arkangel.ai/resources/blog/how-ai-is-revolutionizing-icd-10-coding-accuracy-in-healthca Discover how AI-powered medical coding is transforming ICD-10 accuracy, reducing claim denials, and optimizing revenue cycle performance for healthcare organizations. ### AI-assisted discharge summaries URL: https://arkangel.ai/resources/app/ai-assisted-discharge-summaries-automating-documentation-clinician-efficiency-patient-safety AI auto-drafts discharge summaries to save clinician time, improve accuracy and patient safety. ## Recursos en español ### Inicio URL: https://arkangel.ai/es Language: Spanish (es) La IA procesa registros compatibles, prioriza hallazgos y facilita una revisión auditable. Arkangel AI ayuda a los equipos de salud a detectar oportunidades de ingresos, revisar códigos de diagnóstico y procedimiento, y priorizar hallazgos para revisión humana. ### Precios URL: https://arkangel.ai/es/pricing Language: Spanish (es) Cada plan incluye capacidades completas de revisión de historiales. Comienza gratis y escala desde médicos individuales hasta sistemas de salud empresariales. Obtén inteligencia de historiales completa en cada plan y paga según el valor que capturas. ### IA para médicos URL: https://arkangel.ai/es/ai-for-doctors Language: Spanish (es) Haz una pregunta clínica y obtén una respuesta con estudios revisados por pares. Diseñado para médicos, residentes y equipos que necesitan evidencia verificable en el punto de atención. #### ¿Qué es la IA para médicos? La IA para médicos es software clínico que ayuda a buscar literatura médica, resumir evidencia y redactar razonamiento de planes de cuidado sin reemplazar el juicio clínico. Arkangel AI está diseñada para preguntas médicas: cita fuentes, conserva la incertidumbre y ayuda a pasar de una pregunta específica del paciente a evidencia verificable. ### Investigación URL: https://arkangel.ai/es/research Language: Spanish (es) Descubre artículos de investigación y estudios científicos sobre inteligencia artificial aplicada a la salud, con flujos de investigación creados para equipos clínicos. ### Recursos URL: https://arkangel.ai/es/resources Language: Spanish (es) Recursos educativos y perspectivas para profesionales de la salud: artículos, podcasts, casos de uso, cursos e investigación sobre inteligencia artificial médica. ### Boston Scientific: dispositivos médicos inteligentes con IA URL: https://arkangel.ai/es/resources/podcast/boston-scientific-dispositivos-medicos-ia Language: Spanish (es) Descubre cómo Boston Scientific está integrando inteligencia artificial en sus dispositivos médicos. Laura Velásquez de Arkangel AI conversa con representantes de Boston Scientific sobre dispositivos médicos, innovación en medtech y procedimientos mínimamente invasivos. ### Precisión de la codificación ICD-10 con IA URL: https://arkangel.ai/es/resources/blog/how-ai-is-transforming-icd-10-coding-accuracy-in-healthcare Language: Spanish (es) Descubre cómo la codificación médica impulsada por la IA está transformando la precisión de ICD-10, reduciendo las denegaciones de reclamos y optimizando el rendimiento del ciclo de ingresos. ### Resúmenes de alta asistidos por IA URL: https://arkangel.ai/es/resources/app/resumenes-alta-asistidos-ia-automatizacion-documentacion-eficiencia-personal-medico-seguridad Language: Spanish (es) La IA redacta automáticamente resúmenes de alta para ahorrar tiempo al médico y mejorar la precisión y la seguridad del paciente. Este caso de uso explica cómo automatizar documentación clínica estructurada y reducir la carga administrativa. ## Consultations and solutions ### Free consultation URL: https://arkangel.ai/freeconsultation Book a free consultation with Arkangel AI to explore healthcare AI workflows for your team. ### Arkangel AI vs SAP URL: https://arkangel.ai/arkangel-ai-vs-sap Arkangel AI vs SAP for medical-claims audit in Colombia. For auditing medical claims in Colombia, Arkangel AI runs three independent layers — 27 administrative, 29 clinical and 42 financial rules — and assigns the seven formal causales of Anexo Técnico 6, Resolución 3047 de 2008, per invoice line. SAP is strong ERP and claims-processing software, but it was not designed for that regulatory and clinical adjudication. ### Pharma marketing (ES) URL: https://arkangel.ai/farma-marketing Published in Spanish. Marketing farmacéutico con señal médica real. Arkangel AI convierte preguntas, dudas y barreras clínicas reales de médicos en decisiones de marketing accionables por molécula, patología, especialidad y país. ### Insurers LATAM (ES) URL: https://arkangel.ai/aseguradoras-latam Published in Spanish. Auditoría médica para aseguradoras LATAM. Arkangel AI ayuda a aseguradoras y EPS a revisar cuentas médicas con 98 reglas, tres capas independientes y causales de la Resolución 3047 de 2008.