Clairdoc checks claims before submission, flags payer and documentation issues, and routes only high-risk cases to human reviewers.
Instead of waiting for denials, Clairdoc reviews claims early, flags preventable billing problems, and surfaces only the cases that need human judgment.
Clairdoc is built around the actual places claims break before submission and reimbursement.
Flags coding combinations that can trigger rework or denials.
Validates claims against payer logic before they leave the queue.
Surfaces missing or inconsistent support for the billed claim.
Highlights claims that may need follow-up before submission.
Detects cases where the note and billed claim may not align.
Routes uncertain or high-risk claims to reviewers with context.
Clairdoc combines AI agents, structured billing logic, and escalation workflows so teams can automate routine review without losing control.
Claims and encounter data enter Clairdoc without a heavy implementation project.
Structured billing rules, payer edits, and AI reasoning keep decisions grounded and explainable.
Clairdoc flags denial risk, coding mismatches, and prior auth issues, then routes edge cases to humans.
Corrections, denials, and approvals strengthen the system over time.
Clairdoc surfaces throughput, claim readiness, review pressure, and preventable revenue risk at the queue level.
Queue-level visibility into throughput, review pressure, and denial drivers.
Clairdoc is shaped by live workflow inputs from billing operators, physicians, and specialty-practice teams.
Built with live billing feedback loops, real claims, and human accountability.
Billing teams contribute edge cases and rejection patterns that sharpen the system over time.
Clairdoc is tested against real claims and payer-policy friction.
Routine throughput stays automated while high-risk decisions stay reviewable.
Clairdoc is offering pilots for independent specialty practices ready to move beyond reactive billing cleanup.