Multi-provider AI consensus · ICD-10-AM / ACHI / ACS

Clinical coding for insurance claims — in minutes, not days.

Turn discharge summaries and clinical notes into accurate, audit-ready insurance-claim codes. Built on the Australian ICD-10-AM, ACHI, and ACS standards, with a confidence, rationale, and source quote on every recommendation.

enayacode.app/cases/CASE-20260517 · review
Source clinical text
Male, 62. Presented with chest pain. Diagnosed with acute myocardial infarction. Underwent coronary artery stent insertion via PCI on day 1. Discharged on day 3, stable.
ICD-10-AM I21.4 Acute subendocardial myocardial infarction 94%
ACHI 38306-00 Percutaneous insertion of coronary artery stent 91%
ACS 0940 Acute coronary syndrome — ACS 0940 sequencing rule 88%
Full audit trail 1.8 s · 3 providers agreed
Audit-ready by design Arabic and English UI Tenant-isolated data Multi-provider AI consensus
What you get

Cleaner claims, fewer rejections, defensible at audit

Four capabilities that change how your coding queue actually moves

AI consensus that holds up

Multiple AI providers (Gemini, OpenAI, DeepSeek) vote on each code. Cluster-level agreement plus fail-closed safeguards on insufficient consensus mean fewer hallucinated codes reach the coder — and far fewer reach the payer.

Defensible at audit time

Every code is stamped with a confidence breakdown, rationale, source-quote anchor, provider, model, and prompt version. Payer disputes and internal audits are answered in seconds — not days of back-and-forth.

Bilingual end-to-end

Built for GCC clinical teams that switch languages mid-case. UI, coder workbench, exports, and audit logs all render natively in Arabic (RTL) and English (LTR) — same data, same audit trail, both languages.

Tenant-safe by default

Every query runs through a tenant-scoped manager — defence in depth. Coders, reviewers, payer auditors, and tenant admins only ever see their own data, even if a permission check is missed at the view layer.

Coding tiers

Pick the right tier for each case

Basic for everyday cases, Advanced for high-confidence consensus, Premium when reference grounding matters most

Tier 1

Basic

Single AI assistant — fast, low-cost, moderate confidence.

  • One AI provider per case
  • Confidence + rationale on every code
  • Source-quote highlighting
  • Excel + JSON export
Most popular · Tier 2

Advanced

Multi-model consensus — high confidence, fewer rejections.

  • Multiple AI providers vote per code
  • Cluster-level agreement scoring
  • Fail-closed on insufficient consensus
  • Provider-level audit dashboard
Tier 3 · coming soon

Premium

Reference-grounded coding for the highest-stakes claims.

  • Grounded in licensed clinical reference data
  • ACS sequencing rules enforced
  • Highest confidence and lowest rejection rate
  • Awaiting licensed reference data partnership
Workflow

From file to ready-to-submit claim — in four steps

1
Upload the document

Drop in the discharge summary or operative report as PDF or DOCX — or paste the text.

2
AI analysis

The engine extracts diagnoses and procedures and proposes the right codes with rationales.

3
Coder review

Accept, edit, or reject each code in a two-pane workbench. Every action is captured in the audit trail.

4
Export the claim

Export the claim as Excel or JSON, ready for the insurance payer with a full audit trail attached.

Built for

Who uses EnayaCode?

Hospitals and Clinics

Speed up the claim cycle and reduce rejections.

Clinical Coders

An AI assistant proposes — you approve, edit, or reject.

Insurance Payers

Fast verification with a transparent, immutable audit trail.

Ready to speed up your claims?

Start with a handful of cases — no commitment.

Create your account