Case Studies

At Rheal Software, we continuously look for opportunities to use artificial intelligence and automation to simplify repetitive processes within insurance operations. As part of the ongoing evolution of our Rheal Claims Management System (RhealCMS), we implemented an AI-powered Resume Parser and automated Adjuster Onboarding solution.

The solution transforms the traditional, manual adjuster application process into an automated workflow. From receiving an application through email to extracting information from the resume, validating the data, creating an adjuster profile, and initiating the adjuster's registration, the entire process is orchestrated through cloud-based services and AI.

The result is a faster, more consistent, and scalable approach to bringing new adjusters into the system while significantly reducing administrative effort.

The Challenge

Adjuster onboarding can involve a significant amount of repetitive administrative work, particularly when applications are received through email.

Traditionally, an administrator would need to:

• Monitor a dedicated mailbox for new adjuster applications
• Open and review incoming emails
• Download and review resume attachments
• Manually identify relevant information from resumes
• Enter the information into the Claims Management System
• Create an adjuster account
• Send registration or welcome instructions
• Follow up with the adjuster to complete their profile

This process can become particularly time-consuming when application volumes increase. It can also introduce inconsistencies and data-entry errors because information is manually transferred from an unstructured document into structured system fields.

The goal was to automate this process while retaining appropriate validation and control before an adjuster is officially added to RhealCMS.

The Solution

Rheal designed and implemented an AI-powered, event-driven resume processing and adjuster onboarding workflow.

The solution combines Azure Functions, Azure Blob Storage, AI-based document analysis, and RhealCMS to create an automated pipeline from application receipt to adjuster onboarding.

This architecture allows each stage of the process to operate independently while providing a scalable foundation for future enhancements.

Key Features & Capabilities

1. Automated Email Monitoring

A dedicated email account is used as the entry point for adjuster applications.

An Azure Function periodically monitors the mailbox for new emails and identifies potential adjuster applications based on predefined rules.

The system can evaluate criteria such as:

• New/unprocessed email
• Presence of an attachment
• Supported attachment format
• Sender information
• Application-related email characteristics

This eliminates the need for administrators to continuously monitor the mailbox manually.

2. Automated Resume Identification

Once a new application is identified, the system automatically processes the attached resume.

Supported document formats can include:

• PDF
• Microsoft Word documents
• Other supported resume formats

The original resume is retained and securely stored for future reference and audit purposes.

3. Secure Cloud Document Storage

The resume is uploaded to Azure Blob Storage, providing centralized and scalable document storage.

The system can maintain associated metadata such as:

• Original file name
• Applicant email
• Application date
• Processing status
• Source email information
• Blob storage location

This creates a traceable relationship between the original application, the resume, the AI processing result, and the resulting adjuster profile.

4. AI-Powered Resume Parsing

This is the core of the solution.

Once a resume is uploaded to Blob Storage, an event triggers the resume processing workflow.

The resume is passed to Claude AI, which analyzes the document and extracts relevant information. Instead of simply returning unstructured text, the AI is instructed to return the information in a predefined structured JSON format.

The AI can identify information such as:

• Personal Information – First Name, Last Name, Email, Phone, Address
• Professional Information – Adjuster experience, previous employers, areas of expertise, claim types handled, and industry experience
• Licensing & Certifications – Adjuster licenses, licensed states, certifications, license numbers, and relevant professional credentials
• Skills & Capabilities – Xactimate, Symbility, property claims, auto claims, CAT claims, and other relevant skills
• Education & Additional Information – Education, training, professional affiliations, languages, and other relevant resume information

This converts an unstructured resume into structured data that can be consumed directly by RhealCMS.

5. Structured AI Output

The AI-generated information is returned in a standardized JSON structure.

6. Data Validation & Business Rules

AI-generated information is not automatically treated as final system data.

Before creating an adjuster record, the extracted information goes through validation. The validation layer can verify:

• Required fields
• Email format
• Phone number
• Duplicate adjuster records
• License information
• Required business information
• Data consistency
• RhealCMS business rules

This provides an important layer of control between the AI output and the production database.

7. Automated Adjuster Creation

Once the information successfully passes validation, the system automatically creates the adjuster record in RhealCMS.

The onboarding process can populate relevant sections of the adjuster's profile, including:

• Personal information
• Contact information
• Professional information
• Licenses
• Certifications
• Skills
• Capabilities
• Resume/document information

The original resume can also be associated with the newly created adjuster profile. This eliminates the need for administrators to manually re-enter information from the resume.

8. Automated Welcome & Registration

After the adjuster has been successfully created, RhealCMS automatically initiates the registration process. The system sends a welcome email containing:

• Welcome message
• Login information
• Registration instructions
• Link to the RhealCMS portal
• Instructions for completing the profile

The adjuster can then log into the system and provide any additional information that was not available in the resume.

This creates a seamless transition from application → AI processing → system onboarding → profile completion.

Business Benefits

• Reduced Manual Processing – Administrators no longer need to manually monitor the application mailbox, open every resume, extract information, and enter it into RhealCMS.
• Faster Adjuster Onboarding – Applications can move from email submission to system onboarding automatically, significantly reducing processing time.
• Improved Data Consistency – Structured AI extraction and validation reduce inconsistencies associated with manually transferring information from resumes.
• Reduced Data Entry – Information available in the resume can be automatically populated into the appropriate RhealCMS fields.
• Scalable Processing – The cloud-based architecture can support increasing application volumes without requiring a proportional increase in administrative effort.
• Better User Experience – Adjusters receive their registration information automatically and can proceed directly to completing their profiles.
• AI-Driven Operational Efficiency – The solution demonstrates how AI can be integrated into an existing insurance platform to automate practical business processes rather than functioning as a standalone AI tool.

Conclusion

The AI-Powered Resume Parser and Adjuster Onboarding solution extends RhealCMS with intelligent automation that transforms an otherwise manual administrative process into a streamlined, event-driven workflow.

By combining cloud automation with AI-powered document understanding, Rheal has created a solution that can automatically move an adjuster application from email submission to structured data extraction, validation, system onboarding, and profile completion.

More importantly, the solution establishes a foundation for expanding AI throughout RhealCMS—from intelligent onboarding and profile enrichment to license verification, adjuster capability analysis, and ultimately smarter claim-to-adjuster matching.