Agentic Document Extraction in Legal
Law firms and corporate legal departments process enormous volumes of documents every day — merger agreements, master service agreements, deposition transcripts, due diligence data rooms, court filings, NDAs, lease agreements, and settlement letters, the list goes on.
Manual contract review and extraction introduce inconsistencies that create risk at the clause level — missed renewal dates, overlooked liability caps, and unreviewed change-of-control provisions that compound as portfolios grow.
LandingAI transforms documents into highly accurate, verifiable, structured data so teams can reliably automate document-intensive workflows.
Why Agentic Document Extraction for Legal
Reduce manual document review
Automate data extraction from contracts, legal filings, and case documents to reduce manual review and accelerate legal research and case preparation.
Improve contract and case analysis
Extract key terms, clauses, and structured information from contracts, agreements, and legal documents to streamline analysis and decision-making.
Ensure traceability and compliance
Visual grounding for every extracted field ensures full traceability, enabling legal teams to verify results and maintain defensible audit trails.
Built for Complex Legal Documents
Legal documents are difficult to automate because they often contain dense text, complex clauses, tables, and multi-document case files. Agentic Document Extraction is designed to handle these challenges.
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.
Schema-driven field extraction with visual grounding traceable to the original document.
Strong recognition of multiple languages, handwriting, checkboxes, stamps and signatures.
Use cases
M&A Due Diligence
Extract key terms, defined obligations, governing law provisions, and renewal and termination rights from merger agreements, purchase agreements, employment contracts, MSAs, and NDAs across data room document sets.
Compress due diligence timelines to protect deal schedules and reduce lost-deal risk
Reduce reviewer hours per data room by delivering structured summaries at scale
Ensure consistent clause identification across all reviewers with traceable, auditable output
Contract Review & Obligation Extraction
Extract renewal dates, liability caps, indemnification provisions, termination triggers, and change-of-control clauses from service agreements, licensing agreements, and vendor contracts across an active contract portfolio.
Accelerate contract turnaround to shorten time to revenue on new client engagements
Cut attorney and paralegal hours spent on manual contract intake and abstraction
Reduce exposure from missed renewal deadlines and unreviewed obligation changes
Litigation & eDiscovery
Extract and classify relevant facts, dates, party names, and privileged designations from deposition transcripts, court filings, discovery productions, and correspondence to support early case assessment and document review.
Accelerate early case assessment to inform litigation strategy before costs escalate
Reduce document review costs by narrowing the relevant set before attorney review begins
Maintain privilege integrity with consistent identification and traceable classification decisions
Trusted for Document-Heavy Legal Workflows
Agentic Document Extraction enables legal 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.”
We ran a structured bake-off: the same five PDFs (ranging from a 12-page slide deck to a 400-page machinery manual) processed through other products and Landing AI's Agentic Document Extraction (ADE). We scored each tool on four criteria: Table fidelity, Figure extraction, Chunk typing, Scale. Landing AI ADE was the only tool that scored well on all four.”
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.”
We ran a structured bake-off: the same five PDFs (ranging from a 12-page slide deck to a 400-page machinery manual) processed through other products and Landing AI's Agentic Document Extraction (ADE). We scored each tool on four criteria: Table fidelity, Figure extraction, Chunk typing, Scale. Landing AI ADE was the only tool that scored well on all four.”
