LandingAI ADE and Azure Document Intelligence differ in extraction approach, data retention design, and ecosystem fit. This page compares both for document pipeline decisions.
What Each Product Is
LandingAI Agentic Document Extraction (ADE) converts documents into structured, source-cited data through composable APIs, using a layout-agnostic model that reads any document structure without templates or labeled training data.
| ADE v1 | ADE v2 | |
|---|---|---|
| APIs | Parse, Parse Jobs, Extract, Classify, Section, Split | Parse, Parse Jobs, Extract, Extract Jobs |
| Formats | PDFs, images, Office files, spreadsheets, password-protected PDFs | PDFs and images |
Extraction is schema-driven: you define fields in a JSON schema and change what you extract by editing the schema rather than retraining a model.
Azure Document Intelligence is a cloud extraction service offering two tracks: prebuilt models with fixed schemas for known document types such as invoices, receipts, ID documents, US tax forms, and health insurance cards; and custom models trained on your own labeled data. Custom template and neural models require a labeled dataset of at least five documents of the same type.
Data Retention
| Dimension | LandingAI ADE | Azure Document Intelligence |
|---|---|---|
| Mechanism | Organization-level ZDR setting | 24-hour temporary storage, with a delete API in v4.0 or container deployment |
| Infrastructure required | None, managed SaaS | Container orchestration for zero retention |
| Applies to subprocessors | Yes, when ZDR is on | Depends on deployment |
| Training data storage | Not applicable | Your Azure Blob Storage |
| HIPAA path | ZDR plus a signed BAA | Microsoft DPA and BAA under Enterprise Agreement |
ADE: with the ZDR option enabled, customer data is not persisted beyond processing. Your data is used exclusively to perform the operation you request, and processing ends when the output is returned to you. LandingAI does not use your data for training or improving its models when ZDR is active. ZDR covers the entire platform including all subprocessors, and applies to direct API calls and both the Python and TypeScript libraries. A separate setting extends it to the Playground. ZDR is available on Team and Enterprise plans, in both the US and EU regions.
Azure: results and input are temporarily encrypted and stored in Azure Storage in the request region, then deleted 24 hours after the analyze request. The v4.0 API adds a delete-analyze-response call for earlier removal of results, and container deployment removes cloud storage from the path entirely.
Where Azure Document Intelligence Fits Better
- Microsoft ecosystem: native to Azure, sharing Entra ID authentication, billing, regional infrastructure, and compliance posture with Azure OpenAI, Cognitive Search, Power Platform, Dynamics 365, and Azure Health Data Services.
- Compliance breadth: the Azure platform carries a wide certification portfolio including ISO 27001, ISO 27018, FedRAMP, and PCI DSS. ADE's certifications are SOC 2 Type II, GDPR, and HIPAA conditional on ZDR and a BAA, with the EU-U.S. Data Privacy Framework in progress. Teams with federal, defence, or country-specific requirements should verify both against their own checklist.
- Air-gapped deployment: container deployment to AKS, Azure Container Instances, or customer-managed Kubernetes supports disconnected and edge patterns. ADE's VPC deployment runs inside your own AWS, Azure, or GCP account and assumes cloud connectivity.
- Prebuilt coverage: if your documents match an existing prebuilt schema, you can deploy without designing one.
Where LandingAI ADE Fits Better
- Any document type without training: ADE reads new layouts with no labeled data, no minimum sample count, and no retraining cycle. Azure custom models need at least five labeled documents per type, plus Blob Storage configuration, Studio labeling, and model deployment.
- Retention as an organization-level control: ZDR is enabled once for the organization and applies to every call and every subprocessor, with no pipeline changes or container orchestration to maintain.
- Accuracy on complex layouts: ADE answered 99.16% of DocVQA validation questions correctly, 5,286 of 5,331, from parsed output alone with the image withheld during question answering.
- Grounding on every element: every element ADE detects carries a page reference and bounding box coordinates, and every table cell is grounded independently, so a figure in a multi-level table traces back to its exact cell.
- Line-level detail: text is grounded down to each visual line, for review interfaces that highlight at line level.
- Typed visual elements: ADE detects figures, logos, cards, attestations such as signatures and stamps, and machine-readable scan codes as distinct element types, each grounded in its own right, so those regions are addressable rather than buried in surrounding text.
- Cloud-agnostic: a REST API with Python and TypeScript libraries, presigned URL support across S3, Azure Blob, and GCS, and VPC deployment on any of the three major clouds.
Decision Guidance
Choose Azure Document Intelligence when:
- You are already on Azure and want native integration with Power Platform, Dynamics 365, Azure Health Data Services, FHIR, or Cognitive Search.
- Your document types match Azure's prebuilt coverage and you want to deploy without schema design.
- You need certifications beyond SOC 2, GDPR, and HIPAA, such as FedRAMP or regional standards across an international footprint.
- You need disconnected or fully air-gapped processing via container.
Choose LandingAI ADE when:
- Your document types are variable, novel, or change often, and you need extraction that works without labeled training data.
- Your compliance posture calls for an auditable ZDR control at the organization level, enforceable without infrastructure work.
- Your pipeline is cloud-agnostic or runs on AWS or GCP.
- Your workflows need cell-level table traceability, or extraction from signatures, stamps, logos, ID cards, and barcodes as addressable elements.
- You want to route documents for human review by pointing a reviewer at the exact region a value came from.
FAQ
Does ADE need training data for a new document type?
No. ADE is layout-agnostic and reads any document structure without templates or labeled data. The Extract API takes a JSON schema naming the fields you want, so changing what you extract means editing the schema rather than training a model.
Which product handles HIPAA more simply?
Both support it. Azure requires a Microsoft BAA under an Enterprise Agreement plus customer-managed encryption, regional restrictions, access controls, and audit logging. ADE requires enabling ZDR and signing a BAA, both handled through the platform on Team and Enterprise plans.
How long does each platform hold my documents?
With ZDR enabled, ADE does not persist customer data beyond processing, which ends when the output is returned to you. Azure temporarily stores input and results in Azure Storage and deletes them 24 hours after the analyze request, with a v4.0 delete API for removing results sooner.
Can ADE run on Azure infrastructure?
Yes. ADE deploys as a containerized application inside a customer-managed VPC on Azure, AWS, or GCP, where data stays within your own account.
What file types does each accept?
ADE v2 parses PDFs and images. ADE v1 adds Office files, spreadsheets, and password-protected PDFs. Verify Azure's current format support in Microsoft's documentation.