LandingAI brings its document extraction system to AWS Marketplace as enterprises move beyond OCR
As enterprises move away from legacy OCR systems that struggle with real-world documents, LandingAI is bringing its Agentic Document Extraction (ADE) platform to AWS Marketplace.
The launch allows companies to deploy ADE using existing AWS infrastructure and committed cloud spend, reducing friction between evaluation and production deployment.
👉 https://aws.amazon.com/marketplace/pp/prodview-amiigzbeae4a2
Why OCR and LLM pipelines fall short
For years, document processing has relied on OCR combined with rules or templates. More recently, teams have experimented with LLM-based extraction.
In practice, both approaches tend to break down in production—especially when dealing with large, complex documents such as financial reports, insurance claims, or medical records. These documents often include multi-page tables, inconsistent layouts, and mixed structures that are difficult to process reliably without significant manual intervention.
A schema-driven approach to document extraction
LandingAI’s ADE takes a different approach.
Instead of treating extraction as a free-form task, it uses a schema to define what should be extracted and enforces a consistent structure across documents. The system processes documents holistically rather than splitting them into smaller chunks, which helps maintain context across pages and tables.
Each extracted value is linked back to its source location in the document, including page and region, allowing teams to verify outputs. This is particularly important for workflows that require auditability and traceability.
Built for enterprise deployment
ADE is designed to integrate into enterprise environments and support production-scale workloads.
It supports deployment in cloud or VPC environments, enabling teams to run document processing pipelines within their own infrastructure boundaries. The system is designed to handle high document volumes and large files, including documents with hundreds or thousands of pages.
Because outputs are structured and schema-aligned, ADE can integrate directly into downstream systems such as data pipelines, analytics platforms, and application backends without extensive post-processing.
Key use cases in regulated industries
ADE is being applied to document-heavy workflows across several industries where accuracy and consistency are critical.
In financial services, it is used to extract structured data from bank statements, financial reports, and loan documents to support underwriting and risk analysis.
In healthcare, it processes medical records, claims, and explanation of benefits (EOB) documents, enabling structured data flows into clinical and revenue cycle systems.
In insurance, it is used to extract information from claims, forms, and policy documents, helping automate processing workflows that typically require manual review.
AWS Marketplace as a distribution channel
By launching on AWS Marketplace, LandingAI is aligning with how enterprises increasingly adopt infrastructure and software.
Organizations can use committed AWS spend, consolidate billing, and deploy without introducing a separate procurement process—often one of the primary barriers to adoption for new tools.
A broader shift in document processing
As AI systems become more embedded in enterprise workflows, there is growing demand for structured, reliable data extracted from unstructured documents.
Tools like ADE reflect a shift away from OCR-centric pipelines toward systems that combine document understanding, structured outputs, and traceable results that can be used directly in production systems.
About LandingAI
LandingAI is on a mission to make the world’s documents computable. We are redefining intelligent document processing with Agentic Document Extraction (ADE), an API-first Agentic Document Extraction platform that turns messy, multi-modal documents and dark data into structured, auditable intelligence.