HEALTHCARE PAYER

Claims operations programme for a large US health-benefits company

Claims examiners handle huge volumes of requests across legacy platforms. Wexa built an email-triggered claims-request coworker and designed how a digital claims examiner would work alongside the existing claims engine.

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claims a month in scope
claims examiners the coworker supports
deployment: PHI stays inside the client's cloud
auto-handled share used in the business case
CLIENT
One of the largest US health-benefits companies
REGION
US
WHEN
2025–2026
ENGAGEMENT
Solution build
WEXA COMPONENTS
Email-triggered claims coworker · hosted LLM on the client's cloud · claims-platform integration design

01Case 16

The challenge

  • Very high monthly claims volume
  • Rework and denials from incomplete or inconsistent data
  • Fragmented legacy claims, EDI and mainframe systems

What Wexa built

  • Email-triggered claim-request processor running on a hosted model in the client-approved cloud
  • Design: ingestion coworker for attachments and bills, pre-adjudication assistant, auto-correct and explain, predictive routing
  • Integration design with the existing claims engine, EDI, document management and collaboration tools
  • Knowledge fabric: policy graph, historical claims, feedback loop; immutable audit

02Case 16

How it runs on Wexa

FigureHow this use case runs on Wexa: client systems connected, ontology discovered, context graph in the Wexa memory layer, agents and process flows, and governance. Highlighted components are central to this use case.

03Case 16

Programme architecture

FigureProgramme of coworkers proposed across claims, clinical documentation, quality engineering and member engagement.

04Case 16

Integration with the claims platform

FigureDigital claims examiner working alongside the existing claims engine (redrawn from the project design).

05Case 16

Claims operations layer

FigureAI claims operations layer. Figures on the illustration are design targets.

06Case 16

Results

MeasureBefore / without WexaWith Wexa

Claims examiners for ~40M claims a month

5,000 examiners

3,500 examiners

Annual cost of the process

$350M

$245M

Time to implement the AI solution

13.5 months

16 weeks

AI build cost (one-time)

$3.5M

$355K

AI operating cost per year (models, infrastructure, upkeep, platform)

$5.6M

$2.7M

Total AI cost in year 1

$9.1M

$3M

With Wexa

net annual value to the client after Wexa's own operating cost

faster to implement

lower AI operating cost

less AI spend in year 1

  • Presented at the client's internal technology event (February 2026); discussions continue on a broader scope, including the graph database

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