Autonomously assigns ICD-10, CPT, and HCPCS codes, flags claim risks, and keeps coding current with payer rules — running entirely inside your infrastructure.
The Medical Coding Agent is an autonomous AI agent that reads clinical documentation, assigns accurate ICD-10, CPT, and HCPCS codes, and flags claims at risk of denial before they are submitted.
It connects to your EHR and billing systems, reasons across the encounter and the latest payer rules, and writes coded claims back — without a coder prompting each case.
This is not a coding lookup chatbot. It is an active agent that codes, validates, and escalates edge cases, deployed air-gapped or on-premise so PHI never leaves your environment.
A coding chatbot answers a code lookup when asked. The Medical Coding Agent reads documentation, assigns and validates codes, prevents denials, and writes claims back to your billing system — autonomously, across the full encounter volume.
The Medical Coding Agent is a true AI agent that goes beyond simple Q&A. It reasons, plans, and executes multi-step workflows autonomously while you retain full code ownership and infrastructure control.
Reads clinical notes, operative reports, and encounter data to assign the complete, specific code set for each visit.
When documentation is finalized, the agent assigns codes, checks specificity, and queues the claim — without a coder opening the chart first.
Scores each claim against payer rules, medical necessity criteria, and historical denial patterns before submission.
Flags high-risk claims, attaches the missing documentation requirement, and routes them to a coder only when human judgment is actually needed.
Identifies when documentation does not support the level of service or specificity required for accurate coding.
Generates a targeted physician query for the missing detail and tracks the response, instead of downcoding silently.
Ingests updates to CMS, commercial payer, and LCD/NCD policies and applies them to current coding logic.
When a payer changes a coverage rule, the agent updates its coding logic and re-checks open claims affected by the change.
Cross-references documented services against captured charges to surface missed or under-coded revenue.
Runs nightly reconciliation across encounters, flagging documented but uncoded services for review.
Records the rationale and source documentation for every code assigned, formatted for payer and compliance audits.
On audit request, compiles the evidence packet for each claim — codes, source text, and rule references — ready for submission.
The agent ingests finalized clinical documentation, encounter data, and charge information from the EHR, along with current payer rules and coding guidelines.
It applies multi-step reasoning to map documentation to ICD-10, CPT, and HCPCS codes, checking specificity, medical necessity, and bundling rules.
The agent assigns codes, validates the claim against payer edits, and either posts it to billing or routes documentation gaps and high-risk claims for human review.
It monitors submitted claims, learns from denials and remittance data, and updates its coding logic to prevent the same issue recurring.
The agent maintains a timestamped audit trail and reports coding accuracy, denial rates, and captured revenue to billing and compliance leaders.
Cleared the coding backlog and cut discharged-not-final-billed days by 40% while keeping PHI fully on-premise.
Recovered 6% of previously missed charge revenue and reduced coder time per encounter by half.
Doubled claims-per-coder throughput and reduced first-pass denial rate by 30%.
Eliminated time-based coding errors and reduced telehealth claim rejections to near zero.
Reduced surgical claim denials by 35% and shortened the coding-to-bill cycle by two days.
Deployed air-gapped, maintained teaching-physician compliance, and freed coders for the most complex cases.
Reads finalized documentation, encounters, and charges from Epic and writes coded claims and physician queries back into the workflow.
Connects to Oracle Health to pull clinical documentation and post coded claims, keeping the EHR as the system of record.
Integrates with athenahealth to code encounters and reconcile charges across ambulatory practices.
Reads encounter and documentation data from MEDITECH Expanse and writes back validated codes for billing.
Complements computer-assisted coding and CDI workflows, applying autonomous coding and querying on top of existing tooling.
Posts validated claims to your clearinghouse or PM system and ingests remittance data to learn from denials.
You receive the complete codebase. Your coding infrastructure is yours to audit, modify, and operate permanently — with no black-box SaaS dependency.
Deploy entirely within your own infrastructure. PHI never leaves your perimeter — the cleanest answer to HIPAA data-control requirements.
Run on AWS, Azure, Google Cloud, or your own data centers. ibl.ai is a certified partner of all three hyperscalers.
Choose the model that fits your accuracy and residency needs — Claude, GPT, Gemini, Llama, Mistral, or a fine-tuned clinical model — and swap without rebuilding workflows.
No usage or patient data is sent to ibl.ai. Every coding decision and its rationale is logged to your own immutable audit trail for HIPAA and payer audits.
Pre-submission denial scoring and documentation querying reduce first-pass claim denials by up to 30%.
Autonomous first-pass coding doubles claims processed per credentialed coder by reserving human time for complex cases.
Nightly charge reconciliation recovers revenue from documented but previously uncoded services.
Faster, autonomous coding cuts discharged-not-final-billed days and accelerates cash flow.
Enterprise-wide flat-fee licensing eliminates per-coder SaaS pricing, saving large systems roughly 10x.
See how ibl.ai deploys autonomous AI agents you own and control — on your infrastructure, integrated with your systems.