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Bevaya AI Agent Library
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Submission intake, claims indexing, ACORD extraction, and more — production-ready agents trained for insurance.

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More resources on AI in Premium Audit Processing

Case Study - claims
Research

Page stream segmentation with LLMs

How Bevaya Labs approaches a foundational problem in insurance document AI.

Case Study - claims
Case Study

Workers' comp carrier processes claims 100x faster

How indexing automation delivered 432% ROI in 12 months.

2026.06.02-library-webinar-registration-how-to-establish-clear-ai-ownership-in-your-insurance-organization
Architecture

Inside the Bevaya platform architecture

How specialized models, HITL controls, and integrations come together in production.

How Claim Indexing works · Bevaya
AI Agent · Claims

How the Claim Indexing AI Agent Works

It reads each claim document as it arrives, matches it to the right claim, and routes it to the right adjuster.

Intake Brief
Document INT-884213
Provider invoice · Auto BI · TX
6 pages
2.4s classified
Email channel
Document typeProvider Invoice
Matched claimCLM-4471902
Routed to
Medical Bill Review
matched on claim number and date of loss
Deep Dive

Review the Tasks AI Can Drive

A closer look at each task in claim indexing, and where Bevaya does the work alongside your team.

Presentation mode · press Esc to exit

Example Claim Indexing Task Flow

Handling time 10–15 min
Receive the Submission
Separate the Documents
Splits the packet into its documents, any format
Classify Each Document
Labels each one: bill, demand, report, or correspondence
Capture the Key Details
Pulls claim number, claimant, and dates from the page
Match to the Claim
Looks it up in your claims system (e.g. Guidewire)
?
Claim
found?
If No
Resolve the Match
No-match and low-confidence items go to a reviewer, with the reason
File in the Claim
Stores the document on the claim, under the right type
Route to the Right Queue
Assigns the work to the adjuster or specialty queue
Close Out the Submission
Your teamBevaya AI Agent | Select any step to see the detail