Agentic Document Extraction in Healthcare
Healthcare organizations process millions of documents every day—patient records, insurance claims, referral forms, lab reports, and explanation of benefits (EOB) documents.
Manual document processing slows clinical and administrative workflows and increases operational costs.
LandingAI transforms documents into highly accurate, verifiable, structured data so teams can reliably automate document-intensive workflows.
Why Agentic Document Extraction for
Healthcare
Traceable Outputs for Regulated Workflows
Every extracted value is grounded to a precise location in the source document, giving compliance and operations teams the audit trail that HIPAA reviews, CMS audits, and payer oversight programs require at scale.
Accurate across Clinical Document Complexity
Agentic extraction maintains high accuracy from structured CMS-1500 forms to free-text clinical notes, multi-page discharge summaries, and mixed-format lab reports without format-specific configuration.
Operational Speed at Scale
Compressing document processing cycle times in prior authorization and revenue cycle management reduces administrative delays that directly affect patient access to care and reimbursement speed.
Built for Complex Healthcare Documents
Intelligent document processing across hospital systems, health plans, physician practices, and revenue cycle operations is extremely difficult due to the sheer diversity of document types, the inconsistent layouts and the domain expertise required. This complexity is compounded by multi-language content, handwriting, scanned images, photos, and legacy formats like faxes.
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
Patient Record Processing
Extract key patient information, diagnoses, and treatment data from clinical documentation and medical records.
Faster patient record processing
Reduced administrative workload
Improved data availability for clinical systems
Referral & Intake Document Processing
Extract patient information from referral forms and intake documents to streamline patient onboarding and scheduling workflows.
Faster patient onboarding
Reduced administrative processing time
Improved care coordination
Clinical Doc & Coding
Extract diagnosis codes, procedure codes, and supporting clinical evidence from discharge summaries, operative reports, progress notes, and pathology reports to support accurate medical coding.
Capture all billable services documented in the record to improve net revenue
Reduce coding query volumes and manual review cycles across the coding team
Maintain documentation accuracy that withstands payer and CMS audit scrutiny
Trusted for Document-Heavy Healthcare Workflows
Agentic Document Extraction enables healthcare 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.”
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.”
