Agentic Document Extraction in Insurance
Insurance companies process millions of documents every day — policy applications, inspection reports, claims forms, repair estimates, medical records, police reports, settlement letters, the list goes on.
Manual review slows operations and makes it difficult to scale.
LandingAI transforms documents into highly accurate, verifiable, structured data so teams can reliably automate document-intensive workflows.
Why Agentic Document Extraction for
Insurance
Traceable Outputs at Scale
Every extraction is grounded to a precise location in the source document. At high document volumes, that level of auditability is only achievable through automation.
Accurate across Document Variants
Unlike OCR, agentic extraction understands context and meaning. Accuracy remains high across the full range of real-world document and image quality, not just clean digital forms.
Integrates without Disruption
A single API connection is all it takes to improve document extraction quality for all teams. Staff continue working in the systems they already use.
Built for Complex Insurance Documents
Intelligent document processing across auto, life, P&C and commercial insurance lines is extremely difficult due to the sheer diversity of document types, the inconsistent layouts and the domain expertise required. Then add multiple languages, handwriting, photographs, scans and faxes to the complexity.
Accurate parsing of dense tables that span multiple pages and contain merged cells.
Single pipeline for image, slide, document, and spreadsheet file types with 1000+ pages.
Strong recognition of character-based languages, handwriting, checkboxes, stamps and signatures.
Schema-driven field extraction with visual grounding traceable to the original document.
Use cases
Eligibility Review & Underwriting
Extract applicant and risk data from policy applications, identity documents, inspection reports, vehicle records, medical records, and supporting documentation.
Accelerate time-to-quote and binding, reducing application abandonment
Scale underwriting capacity without proportional headcount growth
Improve risk selection accuracy with complete, consistently extracted applicant data
Claims Processing
Find and verify details required to evaluate and resolve insurance claims across FNOL forms, investigative reports, repair estimates, receipts, and medical bills.
Accelerate claims resolution reducing loss adjustment expenses
Surface fraud and misrepresentation with automated cross-validation 
Ensure consistent, defensible claims decisions with a complete audit trail
Subrogation & Recovery
Extract and organize evidence required to pursue third-party recovery after a claim is paid — title and ownership documents, lien documents, settlement letters, and legal correspondence.
Accelerate evidence assembly to maximize recovery within statute of limitations
Improve recovery rates by ensuring complete, consistent case documentation
Deliver structured case files to analysts automatically, expanding caseload capacity
Trusted for Document-Heavy Insurance Workflows
Agentic Document Extraction enables insurance institutions to automate document-intensive processes that traditionally require manual review.
Very often a loan officer who gets a borrower a solid preapproval fastest earns the deal and the real estate agent’s referrals. Reconstructing income is the hardest part, and Agentic Document Extraction is the cornerstone to getting it right and traceable. Accurate data upfront means we can get a cleaner loan file to the underwriter and get to CTC faster. Get it wrong and everything downstream gets affected.”
View case study →
Agentic Document Extraction has proven to be both accurate and easy to use. We are building on that foundation to deliver reliable, transparent, and scalable automation that our customers can validate and trust.”
View case study →
Trust is the product. Accuracy alone isn’t enough at enterprise scale—what matters is provenance, traceability, and control. LandingAI gives us confidence that every extracted value can be traced back to its source, audited, and defended. That’s what makes it deployable in regulated, real-world environments.”
View case study →Our Plan Review Agent has a lot of complicated components under the hood: traversing building code knowledge graphs, reasoning across disciplines and sheets, assessing issues informed by historical projects. None of it works if we can’t trust what came off the page. ADE gave us a reliable foundation, so our team could focus on incorporating our team’s expertise into our compliance reasoning system.”
View case study →
ADE has significantly outperformed other document extractors we’ve used. It has helped us build an Agentic RAG answer engine, based on unique healthcare institutional content, to offer instant, validated support to medical professionals at the point of care.”
View case study →
We do document parsing for information retrieval and Agentic AI. Agentic Document Extraction has really helped us with our data pipeline. It's powerful, easy to use, well-designed, well-documented, and delivers great extraction performance on unstructured data.”
I appreciate its reliability and the fact that they're constantly innovating with new models, which helps us work smarter. The service is essential for handling heavy workloads in financial institutions as it provides the necessary infrastructure for high accuracy and fast throughput. I also find it adaptable to specific use cases because they're always working on new models.”
We use LandingAI's Agentic Document Extraction to build pipelines that turn unstructured text into structured data. First, the NER (Named Entity Recognition) detection has amazing accuracy. Second, the OCR capability is excellent — earlier I had to run a separate PDF extractor for text plus a separate LLM with OCR to summarize images, and now it's one step. Third, the image boundary detection is a standout.”
We ran a structured bake-off: the same five PDFs (ranging from a 12-page slide deck to a 400-page machinery manual) processed through other products and Landing AI's Agentic Document Extraction (ADE). We scored each tool on four criteria: Table fidelity, Figure extraction, Chunk typing, Scale. Landing AI ADE was the only tool that scored well on all four.”
Very often a loan officer who gets a borrower a solid preapproval fastest earns the deal and the real estate agent’s referrals. Reconstructing income is the hardest part, and Agentic Document Extraction is the cornerstone to getting it right and traceable. Accurate data upfront means we can get a cleaner loan file to the underwriter and get to CTC faster. Get it wrong and everything downstream gets affected.”
View case study →Agentic Document Extraction has proven to be both accurate and easy to use. We are building on that foundation to deliver reliable, transparent, and scalable automation that our customers can validate and trust.”
View case study →Trust is the product. Accuracy alone isn’t enough at enterprise scale—what matters is provenance, traceability, and control. LandingAI gives us confidence that every extracted value can be traced back to its source, audited, and defended. That’s what makes it deployable in regulated, real-world environments.”
View case study →Our Plan Review Agent has a lot of complicated components under the hood: traversing building code knowledge graphs, reasoning across disciplines and sheets, assessing issues informed by historical projects. None of it works if we can’t trust what came off the page. ADE gave us a reliable foundation, so our team could focus on incorporating our team’s expertise into our compliance reasoning system.”
View case study →ADE has significantly outperformed other document extractors we’ve used. It has helped us build an Agentic RAG answer engine, based on unique healthcare institutional content, to offer instant, validated support to medical professionals at the point of care.”
View case study →We do document parsing for information retrieval and Agentic AI. Agentic Document Extraction has really helped us with our data pipeline. It's powerful, easy to use, well-designed, well-documented, and delivers great extraction performance on unstructured data.”
I appreciate its reliability and the fact that they're constantly innovating with new models, which helps us work smarter. The service is essential for handling heavy workloads in financial institutions as it provides the necessary infrastructure for high accuracy and fast throughput. I also find it adaptable to specific use cases because they're always working on new models.”
We use LandingAI's Agentic Document Extraction to build pipelines that turn unstructured text into structured data. First, the NER (Named Entity Recognition) detection has amazing accuracy. Second, the OCR capability is excellent — earlier I had to run a separate PDF extractor for text plus a separate LLM with OCR to summarize images, and now it's one step. Third, the image boundary detection is a standout.”
We ran a structured bake-off: the same five PDFs (ranging from a 12-page slide deck to a 400-page machinery manual) processed through other products and Landing AI's Agentic Document Extraction (ADE). We scored each tool on four criteria: Table fidelity, Figure extraction, Chunk typing, Scale. Landing AI ADE was the only tool that scored well on all four.”
