LandingAI

LandingAI provides agentic APIs for document extraction and processing, turning complex files into structured, auditable data for compliance review, loan processing, plan review, search, and analytics.

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Overview

LandingAI provides Agentic APIs for intelligent document processing, centered on Agentic Document Extraction. The platform is built to turn variable documents into structured data that developers can use in automation pipelines, search, analytics, and AI workflows.

Its core emphasis is accuracy with provenance: outputs include traceable citations, page references, and confidence scores so teams can review extracted data, route exceptions, and use the results in regulated or high-volume document operations.

Core capabilities

Parse into structured output

Convert documents into structured data with layout-aware parsing that preserves text, tables, figures, and hierarchy for downstream automation.

Segment multi-document files

Split long or mixed PDF files into classified sub-documents using document classification and instance detection.

Schema-first field extraction

Extract fields from user-defined schemas, including nested objects, arrays, and large multi-table documents.

Traceable results

Attach page numbers, coordinates, and bounding-box citations so extracted values can be audited against the source.

Confidence scoring

Surface confidence scores to flag outputs that may need human review before they move into downstream workflows.

Developer-friendly delivery

Support modular REST APIs plus Python or TypeScript libraries for document automation pipelines.

Practical use cases

Financial services compliance
Automate client due diligence and KYC document review by extracting ownership, entity, and regulatory data from long, multi-lingual corporate files.
Construction and plan review
Speed up plan review by extracting information from building plans, code-related documents, and other multi-page files that require traceable outputs.
Loan processing
Process loan files faster by turning borrower documents into structured data for underwriting and downstream review.
Search and analytics
Build retrieval and analytics pipelines from document archives by converting unstructured files into queryable, structured datasets.
Operational document workflows
Support compliance checks, reporting, and approval workflows where extracted values need to be auditable and easy to validate.

Pros and Cons

Pros

Provides structured extraction with audit-friendly citations back to the source document.
Handles complex layouts, including tables, figures, scans, and multi-page documents.
Supports splitting, parsing, and field extraction as separate workflow steps.
Offers deployment and security options aimed at regulated environments.
Includes usage-based Explore pricing for evaluation and team/enterprise options for scale.

Cons

The source material does not document every limitation, so fit for a specific workflow still needs validation on sample files.
Pricing and deployment details vary by plan, and some capabilities such as on-premises or VPC deployment are tied to higher-tier offerings.

FAQ

What pricing options does LandingAI offer?

LandingAI’s pricing page describes Explore, Team, and Enterprise plans. Explore is pay-as-you-go, Team is a monthly plan with shared usage, and Enterprise adds custom infrastructure and support options.

How do credits work?

The pricing page says credits are the usage unit. They are consumed when you process a document, and the amount depends on the number of pages in the document.

What kinds of workflows is it used for?

The pricing page lists modular APIs for parsing, splitting, and extracting structured data, and case studies show the platform used for KYC, plan review, and loan processing workflows.

How is LandingAI integrated into existing systems?

The source material does not provide a full setup guide, but it does say the platform can be used through modular REST APIs and Python or TypeScript libraries, with deployment options that include cloud, VPC, and on-premises for Enterprise.

Is it suitable for regulated data?

The source material supports enterprise security controls such as SOC 2 Type II, GDPR and HIPAA compliance by design, zero data retention options, and HIPAA/BAA availability on supported plans.

Quick Facts

Category: Agentic APIs for intelligent document processing
Primary users: Enterprise developers and teams building document automation
Source domain: landing.ai
Core workflow: Parse, split, and extract structured data from documents
Pricing model: Explore pay-as-you-go, Team monthly, Enterprise custom
Deployment options: Cloud, VPC, and on-premises on Enterprise