“This solution eliminated the backlog overnight. Our adjusters finally have the bandwidth to focus on customers.”
VP of Operations, NDA
A regional property and casualty insurance provider was struggling with inefficient claims processing driven by manual document handling. With over 12,000 claims annually — each involving multiple files like police reports, medical records, repair estimates, and photos — adjusters were spending up to 75% of their time on data entry instead of investigation and communication.
Manual workflows created delays, increased errors, and often led to inconsistent customer experiences. Each claim took an average of 3 days just to process supporting documents, slowing settlements and frustrating both employees and policyholders.
Lunari implemented an intelligent document processing system that automated the extraction, validation, and routing of claim data. The result was a shift from slow, manual triage to streamlined, AI-assisted operations without compromising regulatory compliance.
The engagement focused on building a compliant and scalable system to:
Reduce document processing time from 3 days to under 8 hours per claim
Achieve 90%+ accuracy in automated data extraction across all document types
Free up 60% of adjusters’ time for investigation and customer communication
Process 50% more claims annually without increasing headcount
Reduce manual entry errors that delay settlements
Ensure audit-ready compliance and document traceability
Support future growth in both claim volume and document complexity
Lunari delivered the solution in three structured phases:
Document Mapping and Model Training
A dataset of over 1,000 anonymized claim documents was used to identify document types and data fields. OCR and field extraction models were trained and validated using real examples, including scanned forms, photos, and handwritten notes.
Workflow Integration and Automation
The system was integrated via API into the client’s claims management platform. Once documents were uploaded, the assistant extracted structured data such as claimant name, incident date, and policy number. Low-confidence fields were flagged for adjuster review. Batch uploads and smart routing logic ensured smooth handling during peak periods.
Compliance and Optimization
All document flows were mapped to retention policies and logged for audit purposes. Adjusters could correct outputs via a feedback mechanism, which informed periodic model updates managed through CI/CD pipelines.
The solution ran on secure cloud infrastructure with autoscaling enabled during high-volume periods like weather events.
Lunari delivered a secure, scalable system that automated document extraction, validation, and routing across the entire claims workflow. The implementation included four main components:
1. Document Intelligence Engine
OCR system capable of processing scanned PDFs, handwritten notes, and low-quality uploads
Auto-classification for over 30 document types, including police reports, repair estimates, medical records, and incident photos
Field-level extraction for key data points such as policy number, claimant name, damage amount, and incident date
Confidence scoring and flagging for human-in-the-loop review on low-certainty fields
2. Workflow Automation and Claims Integration
Real-time API integration with the client’s claims management system
Automatic population of structured data into existing workflows, eliminating 85% of manual entry
Smart routing of exceptions to specific teams (e.g. medical review, legal)
Batch document ingestion to support bulk uploads during seasonal volume spikes
3. Compliance and Data Security
End-to-end encryption of all documents in transit and at rest
Full audit logging from document intake to final decision
Built-in retention rules and data lifecycle management aligned with insurance regulations
Role-based access ensuring claim data is only visible to authorized personnel
4. Monitoring and Feedback Loop
Live dashboards showing accuracy rates, throughput, and document types processed
In-platform feedback mechanism for adjusters to correct fields and submit edge cases
Regular model tuning cycles based on real-world corrections, managed under controlled CI/CD pipelines
Elastic cloud infrastructure that scales automatically during claim surges (e.g., storm seasons)
The system enabled the client to process high document volumes without compromising data integrity or compliance, and without increasing operational headcount.
Within six months, the system exceeded performance targets and created measurable operational gains.
The system now handles 95% of claim documents autonomously, with human review only for edge cases. The insurer increased claim capacity by over 50% without expanding the claims team, while improving both employee and customer experience.
85%
reduction in document processing time – from 3 days to 8 hours on average
94%
accuracy in automated data extraction across all document types
620K
in annual operational savings, driven by reduced manual processing, faster cycle times, and fewer claim reworks