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For all other types of cookies we need your permission.This site uses different types of cookies. Some cookies are placed by third party services that appear on our pages.You can at any time change or withdraw your consent from the Cookie Declaration on our website.Learn more about who we are, how you can contact us and how we process personal data in our Privacy Policy. Please state your consent ID and date when you contact us regarding your consent. Do not sell or share my personal informationAllow allCustomizeAllow selectionDeny Production-Ready AI for Real-World Documents Convert your documents into accurate, structured data agentically. Fully auditable and traceable with no fine-tuning required. Go from idea to working to pipeline in one day. Start For Free Contact Us Contact Us Start For Free Start For Free Talk to an Expert Built for Production Accuracy you can prove, not guess Agentic Document Extraction (ADE) delivers high accuracy with explicit confidence and audit-ready traceability. Accurate on Complex Docs Built for real-world documents with dense tables, multi-page layouts, and visual structures—not just clean OCR text. All parsed 128 Auditable by Design Every extracted value is grounded to its source with precise coordinates. Confidence scores highlight results that may require review. Autonomous at Scale Process large document volumes with minimal human intervention while maintaining accuracy and traceability. Core building blocks APIs designed for real workflows Modular APIs to parse, split, and extract structured data from any document. Parse Convert variable documents into accurate, auditable structured data LLM-ready Markdown with layout awareness Structured blocks (text, tables, figures) with hierarchy preserved Precise citations for every block (page, coordinates, table-cell grounding) Handles complex layouts: scans, dense tables, forms, multi-format documents Split Automatically segment multi-document files into clean, classified sub-documents. Large-file splitting (handles long, multi-hundred-page batches) Instance detection using repeated identifiers (e.g., invoice number) Boundary overlap handling to keep context when breaks occur mid-page Extract Extract specific fields using schema you define. Schema-first extraction (flat or nested, arrays, multi-table) Large table extraction (thousands of rows across many pages) Auditability by default with bounding-box citations per value Contact Us Start For Free Use cases One platform , endless applications APIs across industries and use cases without rebuilding pipelines for every new document format Financial services Insurance Healthcare Energy & utilities Legal Logistics Financial services Accurately capture key figures, risk indicators, and transaction details, even from complex tables and multi-page documents. Loan & credit underwriting Know your customer (KYC) Regulatory reporting Try with your files Insurance Accurately capture coverage terms, risk details, and line items to accelerate claims, streamline underwriting, and reduce manual review. Risk assessment Claims processing Fraud detection Try with your files Healthcare Extract structured data from complex medical documents while preserving context and supporting compliance requirements. Revenue cycle management(RCM) Medical records processing Clinical research Try with your files Energy & utilities Process highly variable documents at scale, eliminate template maintenance, and feed analytics-ready data into enterprise systems. Regulatory filings Asset management Vendor procurement Try with your files Legal Parse complex layouts and multi-column documents with full traceability, enabling faster review and reliable downstream analysis. Contract review Due diligence (M&A) Regulatory & compliance review Try with your files Logistics Accurately capture shipment details, quantities, line items, and compliance data, even from complex tables and multi-page documents, to accelerate processing, improve tracking accuracy, and reduce manual reconciliation. Shipment validation Customs processing Automated auditing Try with your files Build what comes next Power downstream workflows with structured, traceable outputs. Integrate easily via modular REST APIs and Python or TypeScript libraries. Retrieval-augmented generation (RAG) Accurate retrieval powered by semantic chunking for deeper context. Automation and downstream workflows Reconciliation, compliance checks, reporting, and approvals—without manual reviews. Search and analytics Turn document archives into queryable, structured datasets. Trusted autonomous document processing Built for regulated, high-variance documents where accuracy, traceability, and governance matter. Vision-first Our proprietary vision models reliably extract data from complex tables, dense layouts, and multi-page documents. Our system improves accuracy faster through built-in feedback and control Data-centric Accuracy improves through better, curated data, while failure cases are captured, audited, and systematically fed back to reduce errors and rework. Agentic by design One size doesn’t fit all. Agentic orchestration adapts to each document. Planning, deciding, and verifying until quality thresholds are met. Contact Us Start For Free Enterprise security, startup speed Designed for regulated environments without slowing down teams. SOC 2 Type IICertified secure GDPR & HIPAACompliant by design Flexible DeploymentCloud, on-premises, or virtual private deployment options Data PrivacyZero data retention option Trusted by teams that move fast Trusted by enterprises. Proven with 99.16% DocVQA accuracy. Images and documents processed B+ 1B+ Images and documents processed 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 Business Process Automation Neil WalkerHead of Product, TCG Process 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 Fortune 100 Financial ServiceHead of Data & Analytics, Managing Director 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 HealthTech Platform Dr. Declan KellyCFO, Company X 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 Business Process Automation Neil WalkerHead of Product, TCG Process 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 Fortune 100 Financial ServiceHead of Data & Analytics, Managing Director 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 HealthTech Platform Dr. Declan KellyCFO, Company X 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 Business Process Automation Neil WalkerHead of Product, TCG Process 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 Fortune 100 Financial ServiceHead of Data & Analytics, Managing Director 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 HealthTech Platform Dr. Declan KellyCFO, Company X Questions, answered How is ADE different from OCR + LLM approaches? Most OCR + LLM stacks treat documents as plain text, then ask an LLM to “guess” structure. That breaks on real-world layouts (multi-column pages, nested tables, charts, forms) and makes audits hard.ADE treats documents as visual systems. It extracts text with layout, preserves structure (tables, forms, headings), and returns visually grounded outputs with traceability back to the source—so you can see exactly where each field came from. The result is higher accuracy, fewer brittle heuristics, and better governance for production. What document types does ADE support? ADE can parse multiple file types, including PDFs, images, and spreadsheets. Supported types vary depending on how you use ADE (Playground vs API vs SDKs). For the complete, up-to-date list, see here. What about data privacy and security? Security is a core priority. LandingAI documents its security and privacy posture, including details like security practices, compliance certifications, and a Zero Data Retention (ZDR) option (where available). Learn more here. How does pricing work? ADE is available as monthly and annual subscriptions, and usage is typically measured in credits based on page processing. Full details here. 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For all other types of cookies we need your permission.This site uses different types of cookies. Some cookies are placed by third party services that appear on our pages.You can at any time change or withdraw your consent from the Cookie Declaration on our website.Learn more about who we are, how you can contact us and how we process personal data in our Privacy Policy. Please state your consent ID and date when you contact us regarding your consent. Do not sell or share my personal informationAllow allCustomizeAllow selectionDeny Home | Product DocVQA Benchmark: 99.16% Accuracy Using Agentic Document Extraction Ankit Khare , Shankar Jagadeesan November 12, 2025 Share On : TL;DR We ran on the DocVQA validation split and got 5,286 correct out of 5,331 (99.16%). Of those 45 wrong answers, only 18 are true parsing shortcomings. DocVQA is usually used to evaluate vision-language models, but we are pioneering the use of this popular dataset to establish the accuracy of our Agentic Document Extraction (ADE) Parse API. The key takeaway: an LLM can answer 99.16% of DocVQA questions using only the parsed API response from ADE, with no image access during the QA step. Our latest offering, ADE with the Document Pre-trained Transformer 2 (DPT-2) model, looks at the image once to parse, and it captures the document so completely that the QA step can skip pixels and still be right almost every time. With visual grounding (the bounding boxes and layout that point back to the exact text, tables, figures, and even individual table cells on each page), you parse once, then run unlimited queries against the structured output, and you keep traceability for every answer. We publish representative hard-document successes, all 45 mistakes, and we provide reproducible code for transparency. Benchmarks build confidence; pair them with your data to bulletproof your analysis. We urge you to test ADE on your hardest documents in the playground and tell us where we can improve together to fully automate your document processing pipeline. View Successes and Failures | Access code on GitHub Real Business Value from Accurate Parsing Again, I’d like to drill this key takeaway, when we say we got 99.16% accuracy on DocVQA, we’re not testing a vision-language model, We’re testing whether our parsed output preserves enough information that a human (or LLM) who never saw the original document but saw the parsed representation can still answer questions correctly. Think about what that might might mean: Parse a document once Store the structured output Answer millions of questions from your database Save bucks by never re-processing the images This is how document systems scale. And it’s only feasible if your parsing is exceptional. Remember, parsing doesn’t just mean answering without images, it is how you run document processing pipelines with control and trust: Cost and latency You will need only a single pass through unstructured modality of images/pdf. Everything after that runs on structured data. Provenance and audit Every value you care about links back to the exact span, cell, and page. Human review Bounding Box coordinates and Confidence scores can jump your reviewers to the right spots. Search and analytics Visually Grounded text indexes cleanly for filters, trends, and BI. Schema agility You can always add or change fields anytime without touching pixels again. Privacy and governance. This empowers you to redact spans, enforce retention., share structure, and keep your images private. Better Routing You can use parsed signals to send the hardest 1–2% to a visual model or a human evaluator. Quality Control and Reuse Structured data makes it easier to track parsing quality by section, table, or field over time and reuse the same data for extraction, QA, support, or compliance. RAG and agents Finally, as you might have already guessed, RAG and Agents work better over grounded chunks than over raw images. The Classification of Errors Tells the Real Story Of the 45 errors, only 18 are genuine parsing failures. The rest are either not the typical focus of a parser or errors that can be removed by downstream prompt engineering to get the exact answer. Error Type Count % What It Means Incorrect Parse 13 28.9% OCR/parsing errors (character confusion, misreads). Some of the images are really tricky due to occlusions and terrible scans, but we are continuously improving and excelling even over the hardest edge cases with each model release Prompt/LLM Misses 18 40% Reasoning or interpretation failures. Your downstream heuristics or careful prompt design can easily tackle these misses. Not ADE Focus 9 20% Spatial layout questions outside any Parser’s core focus Missed Parse 5 11.1% Information not extracted during parsing. There are certain cases where the parser misses to extract. Devil is in the details, I recommend you taking a look at these examples to understand why it’s missed. Dataset Issues 18 — Questionable ground truth (excluded from count and accuracy calculation) Our VQA Approach is Even Harder It becomes quickly imperative that getting everything extracted from the document irrespective of the questions asked is harder as compared to standard DocVQA: Standard VQA systems: Take (image + question) Feed to vision-language model Get an answer Our approach: Parse document to get the output; you get both a markdown and a JSON representation. Answer all questions from md/json without the image Answering Questions We used ADE Playground to answer questions from the parsed output. The playground pipeline never sees the original images, only refers to the extracted markdown output. For evaluation, we performed the exact string match (case-insensitive) exactly as per the official DocVQA evaluation. The Journey to 99.16% Version Method Accuracy Input Baseline ADE Playground Chat 95.36% Markdown output from ADE’s DPT-2 model Final ADE Playground Chat + Guided prompting 99.16% Markdown + Visual Grounding information from DPT-2 model The improvement came from: Using JSON output instead of markdown because our JSON has baked in spatial information (visual grounding) not just extracted text Optimized prompt structure for better question interpretation and guiding the playground app to better understand how to leverage the parsed output for some of the tricky documents in the DocVQA dataset, refer to the additional reading section at the end or the gallery for examples. Note: you can replicate the results by choosing an LLM to replace our playground chat feature. About DocVQA DocVQA is a question-answering benchmark on real scanned documents from the UCSF Industry Documents Library. Created by researchers at UC San Diego and Allen Institute for AI, it’s designed to test document understanding capabilities. Validation set: 5,349 questions across 1,286 document images Question types: Factual extraction, spatial reasoning, table understanding Evaluation: Exact string match (case-insensitive) Current leaderboard (test set, October 2024): Qwen2-VL: 97.25% (with image access) Human baseline: ~96-98% (estimated) Our result: 99.16% (on validation set using ADE’s DPT-2 model) The next step is to release the results on the test set in the near future. Based on validation performance and the similar statistical distribution of data and complexity of the documents, we expect similar state-of-the-art results. Complete Transparency: Every shortcoming is accessible In AI/ML it’s widely recognized that benchmarks can be “gamed.” Trust is not built by hiding or deceiving so we make sure we strive for utmost transparency by publishing the verifiable misses and the code. We include: Interactive gallery with all 45 errors and 63 out of 5,331 correct answers Source code to reproduce everything A detailed breakdown for each result, with images, predictions, ground truth, question IDs, and classified shortcomings in the interactive gallery You can evaluate for yourself whether these errors matter for your use case. Again, this is about building trust. We want you to see exactly what document parsing can do today, what it can’t do, and where the remaining challenges are. Try It Yourself Want to see how ADE parsing performs on your documents? Try Agentic Document Extraction (ADE): va.landing.ai Questions? Contact us Join our Discord Community to get instant support and chat with fellow Document AI enthusiasts. Download post as PDF Table Of Content 01 TL;DR02 Real Business Value from Accurate Parsing03 The Classification of Errors Tells the Real Story04 Our VQA Approach is Even Harder01 Answering Questions05 The Journey to 99.16%06 About DocVQA07 Complete Transparency: Every shortcoming is accessible08 Try It Yourself Related Posts The ADE Storybook Part 2: The Splitter How to Build Accounts Payable Automation Without Replacing Your Finance Stack Introducing Confidence Scores: Surface Parsing Uncertainty Before It Becomes a Problem Product Industries Resources Developers Pricing Company Log in Start For Free Back to main menu PRODUCT Agentic Document Extraction Extracts structured data from any document LandingLens End-to-end Visual AI platform for training and deploying vision models Snowflake Native Apps Agentic Document Extraction and LandingLens as a Native App Back to main menu RESOURCES Docs Blogs Webinars & Events Become a Builder Trust Center Circle Community All Resources DEVELOPER Github Python Library Discord Circle Forum Youtube Back to main menu SOLUTIONS Agentic Document Extraction in Financial Services Turn complex financial documents into actionable insights Agentic Document Extraction in Healthcare Automate patient intake, medical forms, lab reports INDUSTRIES Automotive Electronics Food & Beverage Medical Devices Life Sciences Agriculture Manufacturing Infrastructure Pharma EV Manufacturing Semiconductor Back to Home PRICING Choose a platform to continue Agentic Document Extraction A new suite of agentic vision APIs — document extraction, object detection, and more. LandingLens An end-to-end, low-code platform to label, train, and deploy custom vision models. Back to main menu COMPANY About Us Careers Contact Us Back to Home LOGIN Choose a platform to continue Agentic Document Extraction A new suite of agentic vision APIs — document extraction, object detection, and more. LandingLens An end-to-end, low-code platform to label, train, and deploy custom vision models. Back to Home START FOR FREE Choose a platform to continue Agentic Vision APIs A new suite of agentic vision APIs — document extraction, object detection, and more. LandingLens An end-to-end, low-code platform to label, train, and deploy custom vision models. Back to main menu DEVELOPERS Docs Github Python Library Get In Touch Start For Free COMPANY About Us Careers Contact Us SOLUTIONS Agentic Document Extraction in Financial Services Turn complex financial documents into actionable insights Agentic Document Extraction in Healthcare Automate patient intake, medical forms, lab reports PRODUCT Agentic Document Extraction Extracts structured data from any document LandingLens End-to-end Visual AI platform for training and deploying vision models Apps in Snowflake Agentic Document Extraction and LandingLens RESOURCES Docs Blogs Webinars Trust Center Become a Builder Discord Circle Forum --- We value your privacyWe use tools to track, analyze, and personalize your experience. Some are essential for this site to function; others help us understand how you use the site, so we can improve it. We may also use cookies for targeting purposes. Click “Accept all” to proceed as specified, or click “Decline non-essential” to only allow a minimal set of tools. To find out more about the cookies we use, see our Privacy Policy.Accept AllDecline Non-Essential Blog All Posts Product Case Study Will It Extract Tutorial News Search for: Tutorial The ADE Storybook Part 2: The Splitter Ava Xia March 13, 2026 In the Kingdom of Unstructured Data, things are rarely that tidy. Often, you will be handed a "Packet"—a 50-page PDF containing Invoices, Pay Stubs and Bank Statements all scanned together into one messy file. If you try to extract an "Invoice Number" from a Bank Statement, your commands will fail. Product How to Build Accounts Payable Automation Without Replacing Your Finance Stack Nitish Dandu , Ankit Khare March 13, 2026 Most companies pay $12.88 to process a single invoice. The best pay $2.78. The difference isn't better software — it's a better workflow. Product Introducing Confidence Scores: Surface Parsing Uncertainty Before It Becomes a Problem Bianca Ragsdale March 11, 2026 The Problem with Trusting Document AI Blindly When you build a document processing pipeline, you’re making an implicit bet: that when the model reads an invoice, a contract, or a financial statement, it gets the right answer. Most of the time, it does. But “most of the time” is exactly where the problem lives. Document […] Tutorial The ADE Storybook: A Developer’s Guide to Taming Documents Ava Xia March 3, 2026 Welcome to the Kingdom of Unstructured Data, a messy place filled with documents like invoices, bank statements, engineering diagrams, and forms. Your task is to take this chaotic mountain of files and turn them into readable, structured data for automated workflows. Case Study How a Global Tier-1 Bank Transformed Client Due Diligence with LandingAI Grace Lee February 9, 2026 A global Tier-1 financial institution modernized its Client Due Diligence (CDD) operations within their Know Your Customer (KYC) process by deploying Agentic Document Extraction. Facing rising document volumes, manual review bottlenecks, and increasing regulatory pressure & complexity, the bank introduced AI-driven document intelligence to augment analysts and streamline complex KYC workflows. The solution automated extraction […] News LandingAI Partners with Snowflake to Accelerate AI-Driven Energy Operations LandingAI Team January 27, 2026 LandingAI collaborates with Snowflake to deliver agentic document extraction into the AI Data Cloud, enabling energy organizations to accelerate modernization, improve resiliency, and harness AI-driven insights at scale Tutorial Document AI: From OCR to Agentic Doc Extraction LandingAI , DeepLearning.AI January 27, 2026 Join this new short course on Document AI, built with LandingAI and taught by David Park, Senior Director of Applied AI, and Andrea Kropp, Applied AI Engineer at LandingAI. Product From Zero to Automated Document Workflows: Hands-on with OCTO & Agentic Document Extraction LandingAI , TCG January 16, 2026 AI extraction has reached a turning point. Models can now reason through document structure and variation with minimal configuration—which means the real opportunity lies in how quickly organizations can deploy that intelligence at scale, inside a secure, controlled environment. Product Splitting Multi-Document PDFs at Scale with ADE Split Bianca Ragsdale December 28, 2025 ADE Split helps teams handle multi-document PDFs by separating parsed files into classified sub-documents. Learn how Split Rules enable accurate and scalable document processing across complex PDFs. 1 2 3 … 6 Next » --- We value your privacyWe use tools to track, analyze, and personalize your experience. Some are essential for this site to function; others help us understand how you use the site, so we can improve it. We may also use cookies for targeting purposes. Click “Accept all” to proceed as specified, or click “Decline non-essential” to only allow a minimal set of tools. 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For all other types of cookies we need your permission.This site uses different types of cookies. Some cookies are placed by third party services that appear on our pages.You can at any time change or withdraw your consent from the Cookie Declaration on our website.Learn more about who we are, how you can contact us and how we process personal data in our Privacy Policy. Please state your consent ID and date when you contact us regarding your consent. Do not sell or share my personal informationAllow allCustomizeAllow selectionDeny Agentic Document Extraction Choose The Plan That Is Right For You Monthly Plan Annual Plan Save 10% Explore Team Visionary Enterprise Explore Personal account — no team features Pay-as-you-go $1 buys 100 credits Perfect for developers building prototypes. Start for Free Start with 1000 free credits Includes Core Capabilities Parse Intelligent chunking and layout understanding with correct reading order — accurately handles text, tables, charts, images, graphs, forms, equations, etc. Field extraction Visual groundingTrace results back to exact regions in the document. Document splitting & classification Multilingual documents API & library access Team Personal account — no team features $ $ 250 / month 27.5k credits / month 27.5k credits $ 250 month 55k credits $ 500 month 110k credits $ 1,000 month 165k credits $ 1,500 month For overages, charge $0.01 per credit. $1 buys 110 credits +10% more Built for collaborative teams. Continue Everything in Explore, Plus: Organization Support Team management and shared usage Supports unlimited users. Unlimited API key creation with usage tracking Email support Security Zero data retention available HIPAA-compliant processing with BAA agreement available Visionary Personal account — no team features $ $ 2,000 / month 260k credits / month 260k credits $ 2,000 month 455k credits $ 3,500 month 650k credits $ 5,000 month For overages, charge $0.01 per credit. $1 buys 130 credits +30% more Designed for high-volume processing. Continue Everything in Team, plus: Advanced Organization Support Team management and shared usage Supports unlimited users. Confidence scoring See how confident the model is in each extracted value — for review, QA, and automation decisions. Slack support Enterprise Personal account — no team features Custom Credit volume matched to your needs Tailored pricing, support, and deployment options For enterprises with advanced needs. Contact Us Everything in Visionary, plus: Security & Compliance SaaS, VPL (Virtual Private LandingAI), VPC, and on-prem deployments Enterprise Document Processing Custom processing pipeline SLAs and uptime guarantees Priority rate limits Snowflake integration support Explore Personal account — no team features Pay-as-you-go $1 buys 100 credits Perfect for individuals building prototypes. Start for Free Start with 500 free credits Includes Core Capabilities ParseIntelligent chunking and layout understanding with correct reading order — accurately handles text, tables, charts, images, graphs, forms, equations, etc. Field extraction Visual groundingTrace results back to exact regions in the document. Document splitting & classification Multilingual documents API & library access Team $3,000 $ 2,700 / year 330k credits / year 330k credits $ 2,700 year 660k credits $ 5,400 year 1,320k credits $ 10,800 year 1,980k credits $ 16,200 year For overages, charge $0.01 per credit. $1 buys 110 122 credits +10% more Built for collaborative teams. Continue Everything in Explore, Plus: Organization Support Team management and shared usage Supports unlimited users. Unlimited API key creation with usage tracking Security Zero data retention available HIPAA-compliant processing with BAA agreement available Visionary $24,000 $ 21,600 / year 3,120k credits / year 3,120k credits $ 21,600 year 5,460k credits $ 37,800 year 7,800k credits $ 54,000 year For overages, charge $0.01 per credit. $1 buys 130 144 credits +30% more Designed for high-volume processing. Continue Everything in Team, plus: Advanced Organization Support Team management and shared usage Supports unlimited users. Confidence scoring See how confident the model is in each extracted value — for review, QA, and automation decisions. Slack support Enterprise Personal account — no team features Custom Credit volume matched to your needs Tailored pricing, support, and deployment options Contact Us Everything in Visionary, plus: Security & Compliance SaaS, VPL (Virtual Private LandingAI), VPC, and on-prem deployments For enterprises with advanced needs. Enterprise Document Processing Custom processing pipeline SLAs and uptime guarantees Priority rate limits Snowflake integration support * This price applies to the US; for European Union (EU) pricing, please check here. How do credits work? Features Explore Team Visionary Enterprise Core Features Parsing View Supported File Formats Intelligent Chunking Field extraction List Extraction Table Extraction Visual Grounding Figures Summaries Confidence Scoring Multilingual documents Custom Processing Pipeline Organization Support Seats 1 Unlimited Unlimited Unlimited Support Level Community Enhanced Priority Designated Security & Deployment Rate limits Standard rate limits Higher rate limits Premium rate limits Priority rate limits Zero Data Retention HIPAA/BAA (include ZDR) VPC and On Prem Deployments SLA & Uptimes Other available APIs FAQs How do credits work? Credits are usage units that get consumed each time you process a document. Every document processing task—like parsing or field extraction—uses credits based on the number of pages in the document. If you’re on the Explore plan, you can buy credits on a pay-as-you-go basis. If you’re on the Team, Visionary, or Enterprise plan, you get a monthly allotment of credits. Is ADE compliant with HIPAA? ADE supports HIPAA compliance on its Team, Visionary, and Enterprise plans. To ensure HIPAA compliance, you must: Enable the Zero Data Retention (ZDR) option. Have a signed Business Associate Agreement (BAA) in place with LandingAI. To initiate the BAA process, submit your request through the form on the Organization Settings page (available after ZDR is enabled). To learn more about our HIPAA compliance, check out our Trust Center and Security & Compliance page. Does ADE support Zero Data Retention (ZDR)? ADE supports zero data retention (ZDR) on its Team, Visionary, and Enterprise plans. To learn more about the ZDR option, check out our docs. Is ADE compliant with SOC2 Type II? LandingAI is SOC 2 Type II compliant. To learn more, check out our Trust Center and Security & Compliance page. Where can I learn more? We offer several resources to help you learn more about Agentic Document Extraction: Documentation: Learn how to use our library and API to quickly get up to speed on ADE. Discord: Share your scripts, ask questions, and get feedback from other programmers in our developer-focused Discord server. Scripts & Demos: Use our repo of scripts and notebooks to guide you through real-world document extraction use cases. YouTube: Watch demos and video tutorials from our Machine Learning Experts. Plus, get the latest feature announcements from Dr. Andrew Ng! Community: Join the LandingAI community to connect with other users and get the latest updates. If you have additional questions, contact us at support@landing.ai. Product Industries Resources Developers Pricing Company Log in Start For Free Back to main menu PRODUCT Agentic Document Extraction Extracts structured data from any document LandingLens End-to-end Visual AI platform for training and deploying vision models Snowflake Native Apps Agentic Document Extraction and LandingLens as a Native App Back to main menu RESOURCES Docs Blogs Webinars & Events Become a Builder Trust Center Circle Community All Resources DEVELOPER Github Python Library Discord Circle Forum Youtube Back to main menu SOLUTIONS Agentic Document Extraction in Financial Services Turn complex financial documents into actionable insights Agentic Document Extraction in Healthcare Automate patient intake, medical forms, lab reports INDUSTRIES Automotive Electronics Food & Beverage Medical Devices Life Sciences Agriculture Manufacturing Infrastructure Pharma EV Manufacturing Semiconductor Back to Home PRICING Choose a platform to continue Agentic Document Extraction A new suite of agentic vision APIs — document extraction, object detection, and more. LandingLens An end-to-end, low-code platform to label, train, and deploy custom vision models. Back to main menu COMPANY About Us Careers Contact Us Back to Home LOGIN Choose a platform to continue Agentic Document Extraction A new suite of agentic vision APIs — document extraction, object detection, and more. LandingLens An end-to-end, low-code platform to label, train, and deploy custom vision models. Back to Home START FOR FREE Choose a platform to continue Agentic Vision APIs A new suite of agentic vision APIs — document extraction, object detection, and more. LandingLens An end-to-end, low-code platform to label, train, and deploy custom vision models. Back to main menu DEVELOPERS Docs Github Python Library Get In Touch Start For Free COMPANY About Us Careers Contact Us SOLUTIONS Agentic Document Extraction in Financial Services Turn complex financial documents into actionable insights Agentic Document Extraction in Healthcare Automate patient intake, medical forms, lab reports PRODUCT Agentic Document Extraction Extracts structured data from any document LandingLens End-to-end Visual AI platform for training and deploying vision models Apps in Snowflake Agentic Document Extraction and LandingLens RESOURCES Docs Blogs Webinars Trust Center Become a Builder Discord Circle Forum
