Works along with your existing systems, retrieving payer context and coordinating revenue decisions with agentic RAG
Every claim evaluated by Axora follows the same decision loop before submission
Axora retrieves the full claim context before any decision is made.
Specialized AI agents evaluate claim readiness using the same grounded context.
When inconsistencies appear, Axora routes precise corrections directly into the workflow.
Remittance outcomes continuously strengthen the decision engine.
How Axora Platform Works
Seven specialized agents evaluate signals across the revenue cycle and coordinate revenue decisions as encounters move from access through payment and financial reconciliation.
Signals detected in one stage inform the next, allowing risks to surface earlier and corrections to occur before they reach the payer.
Every signal includes the policy, documentation context, and claim element that triggered it, along with the next recommended action.
Every flagged claim comes with the exact evidence trail — the policy rule, the documentation gap, the affected code, and a clear next step. No guessing, no manual investigation
Medical necessity risk for CPT 99215
Payer guideline: Medical Necessity Rule 12.3
Diagnosis code does not support procedure requirements
Review documentation before claim submission
Use your claim volume and denial rate to model revenue at risk
$0
*Based On Your Inputs And Conservative Industry BenchmarksAxora is EHR-agnostic by design, without the need for replacing or deeply coupling with your existing infrastructure. It functions as an intelligent layer that sits alongside your current EHR and workflows.
Before a claim is submitted, Axora runs it through a coordinated review across eligibility, authorisation, medical necessity, clinical documentation, and coding accuracy. Each check draws on payer-specific rules, clinical context from the patient record, and historical patterns from similar claims. Where a gap or conflict is identified, Axora traces it to a specific cause and surfaces it for the relevant team to resolve. Every flag comes with a reason, so teams know exactly what needs to change and can act with confidence rather than guesswork.
Revenue cycle breakdowns often happen at the handoff between clinical documentation, billing, and payer submission. Axora sits across all three simultaneously, pulling clinical context, billing status, and payer requirements into a single review layer. A coding gap identified in clinical notes gets flagged to the right team before it becomes a billing error. A payer requirement gets checked against the claim before submission rather than after rejection. Teams see the output and the recommended action, not the complexity happening in the background.
Axora identifies six categories of pre-submission risk. The first is eligibility and coverage gaps that would make a claim unbillable. The second is missing or incomplete prior authorisation. The third is medical necessity misalignments between clinical documentation and payer criteria. The fourth is undercaptured diagnoses that affect DRG reimbursement. The fifth is coding inconsistencies across primary and secondary diagnoses. The sixth is claim-level conflicts with payer-specific submission rules. Each risk type is handled by a dedicated agent, so detection is specific and the recommended resolution is tied to the exact issue found.
When Axora identifies a risk in a claim, it surfaces the specific reason alongside the flag, a missing authorisation reference, a documentation gap affecting medical necessity, a coding conflict with payer rules. Teams are not working from a rejection notification after the fact. They are working from a pre-submission explanation that tells them exactly what to fix and where. This is what makes resolution faster and more consistent across billing teams, particularly in multi-facility environments where standardising decision-making is operationally difficult.
Axora evaluates claims in parallel across the full submission pipeline, so review does not become a bottleneck as claim volumes increase. For multi-facility hospital groups or health systems processing high daily claim counts, this means risk identification scales with the workload rather than depending on manual capacity. Teams are surfaced only what needs attention, with the highest-risk claims prioritised, so effort is concentrated where it has the most impact on reimbursement outcomes.
