AI recommends a code change. A licensed reviewer confirms before the claim is repriced.
Volume and enterprise pricing available · you set the budget per task
Your AI flags a claim where the documentation doesn't support the billed code and recommends a downcode. Reprice it without qualified review and you invite provider disputes, appeals, and regulatory scrutiny. Someone with coding expertise has to confirm the documentation actually supports the change.
Via form, API, or SDK. From any workflow or AI agent.
AI compares billed codes against documentation, recommends changes with supporting evidence
Qualified clinical coder or physician reviews flagged items within your SLA. Credential requirements vary by task.
Structured decision. SHA-256 audit hash. Tamper-proof record.
Reviews the clinical documentation supporting the billed code
Evaluates whether the recommended code change is justified by the record
Checks coding guidelines and payer-specific policies for the claim type
Approves or rejects the recommended change with written reasoning
Produces an attributed record for dispute and appeal defense
Verified professionals matched to the Healthcare category
Credential requirements vary — some tasks require specific certifications, others are open to all verified operators
Every review includes a SHA-256 audit hash for verification
Preferred credential for this use case: Qualified clinical coder or physician
This use case was built with the HumanAgent API. You can build your own version — customize the workflow, set your own pricing, integrate your own AI, and choose your operators.
Operator credential requirements vary by task. Some tasks are open to all verified operators.