DocuOCR reads the documents a legal team works with, classifies each one, and pulls the parties, dates, terms, and amounts you need, straight from contracts, court filings, discovery records, and legal invoices. No template to build, no keying by hand.
Built for US law firms, corporate legal departments, legal operations teams, title companies, and legal process outsourcers that handle documents at volume and cannot afford a misread term.
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Drop in a contract, pleading, or legal invoice to watch DocuOCR read it and pull out the data, free, no signup required.
Legal work runs on documents, and a single matter generates a stack of them. The signed contract and its amendments, the pleadings and motions filed with the court, the discovery set with hundreds of exhibits, the corporate records, the lease or deed, the vendor invoices that follow. Someone has to read all of it, find the parties, dates, dollar amounts, and key terms that matter, and put them where the team can use them. That review is slow, it repeats on every matter, and it is expensive when a paralegal or associate is doing it by hand.
Legal document processing software takes the keying off your team. It reads each document, identifies what it is, and extracts the fields legal staff depend on, the parties and counsel, the effective and expiration dates, the renewal and termination terms, the governing law, the amounts, the case and docket numbers, then checks the values before they reach a matter file. Instead of typing data out of a scan, your team reviews what the software already pulled.
The change that makes this practical is AI. Older tools needed a separate template for every contract or form and broke the moment a layout changed. Modern extraction reads a document by understanding its structure and clause language, so an unfamiliar agreement or a faxed court filing does not stop the line. That is the difference between software that adds review work and software that clears it.
DocuOCR classifies and extracts the legal documents that fill a matter file, however they arrive: native PDFs, scans, or faxes.
Reads parties, effective and expiration dates, renewal and termination terms, governing law, payment terms, and amounts from MSAs, NDAs, SOWs, and amendments in any format.
Captures case number, court, parties, counsel, filing dates, and docket references from complaints, motions, orders, and filed exhibits.
Reads and indexes large exhibit and production sets, pulling dates, names, and key references so litigation teams can search a file instead of paging through it.
Extracts entity names, officers, formation and amendment dates, and signatory details from bylaws, operating agreements, and board minutes.
Pulls grantor and grantee, legal description references, recording data, dates, and rent or consideration amounts from deeds, leases, and title records.
Reads matter numbers, timekeepers, rates, line items, and totals from outside-counsel invoices and engagement letters for review and accrual.
Outside-counsel and vendor invoices often need their timekeepers and line items broken out on their own for billing review and accrual. If you want legal invoices specifically pulled into structured, spreadsheet-ready line items outside the matter workflow, our focused legal billing to Excel converter handles that one task, while DocuOCR processes the whole matter file end to end.
Classify, read, extract, validate. Drop a matter file in and the whole sequence runs on its own.
The engine reads a mixed stack of pages and sorts them by document type, contract, pleading, exhibit, corporate record, invoice, so the right extraction runs on each.
OCR and ICR convert scans, faxes, and image-only PDFs into machine-readable text, including hand-completed fields, stamps, and signatures.
DocuOCR pulls the legal fields tied to their clauses and labels, so you get named values, dates, parties, and tables instead of a wall of text.
Values run through your rules and cross-document checks, low-confidence reads route to review, and clean data exports to your DMS, CLM, or practice management system.
# msa_executed.pdf -> extracted data { "document_type": "master_services_agreement", "party_1": "Northgate Systems, Inc.", "party_2": "Brightlane Analytics LLC", "effective_date": "2026-03-01", "term_months": 24, "auto_renewal": true, "governing_law": "Delaware", "confidence": 0.98 } # classified, read, validated, ready for the matter
Reading a clean PDF contract is the easy part. These are the capabilities that decide whether the software actually clears a legal team's review queue.
Sorts a multi-document file by type automatically, so no one separates contracts, pleadings, exhibits, and invoices by hand before processing can start.
Reads MSAs, NDAs, leases, SOWs, and amendments from any source without a per-document template, so a new counterparty form does not break the flow.
Pulls parties, dates, governing law, renewal and termination terms, and amounts as named fields, not buried text, so review starts from data.
Reads hand-completed fields, stamps, and signature blocks with intelligent character recognition, routing low-confidence reads to a reviewer.
Processes large exhibit and production sets in bulk, so litigation support can index and search a case file instead of opening every page.
Encryption in transit and at rest, role-based access, audit logs, configurable retention, and US data handling for privileged, client-confidential files.
The cost of manual review is not just billable hours. It is the missed renewal date, the term keyed wrong into a matter, and the discovery set no one can search when a deadline lands.
| Factor | Automated (DocuOCR) | Manual review |
|---|---|---|
| Time per document | Seconds to read and extract | 20+ minutes of reading and keying |
| Sorting the file | Classified automatically | Pages separated by hand |
| Missed dates and terms | Flagged at capture | Caught after a deadline passes |
| New contract formats | Read on the first pass | Re-learned by each reviewer |
| Discovery volume | Indexed and searchable in bulk | Reviewed page by page |
| Data into DMS or CLM | Exported or pushed by API | Retyped at the handoff |
DocuOCR is built on intelligent document processing: it classifies the file, reads any contract or filing layout, extracts the data, and validates it across documents, so legal teams review data instead of retyping it.
Any team that reads legal documents to move a matter forward gets time back.
Classify mixed matter files, extract contract terms and case data, and load clean records into the document management system instead of keying every file by hand.
Read incoming contracts and counterparty paper, pull key dates and obligations, and track renewals and risk without reviewing every clause manually.
Standardize how documents become data across the department, so reporting, contract tracking, and accruals draw from clean structured fields.
Read deeds, leases, and title documents to capture parties, legal references, and recording data faster across a high volume of closings.
Index large discovery and production sets in bulk so reviewers search a case file by data instead of opening every exhibit.
Call the API to add document classification and legal data extraction to your own CLM, e-discovery, or practice management product.
Run documents by hand in the dashboard, or call the same engine from your CLM, e-discovery, or practice management platform with one REST request. Post a document and get back the classified type, the recognized text, and the extracted fields, with a confidence score on every value.
# classify + extract a legal document curl https://api.docuocr.com/v1/extract \ -H "Authorization: Bearer $KEY" \ -F "[email protected]" \ -F "classify=true" # -> document type + fields + confidence
No seat licenses and no setup fees. Start free to check accuracy on your own contracts and filings, then pay per page as your volume grows. Higher volumes move to committed plans with lower per-page rates and priority throughput.
The questions legal and operations teams ask most before they automate legal document processing.
Legal document processing software reads the documents a legal team works with, identifies what each one is, and extracts the data into structured fields. It handles contracts, agreements, court filings, discovery records, deeds, and legal invoices, then validates the values before they reach a matter file or system. Instead of paralegals and associates keying terms, dates, and parties from scans and PDFs, the software pulls them and routes anything uncertain to review.
OCR for legal documents converts scanned contracts, pleadings, and case files into searchable, machine-readable text, then pulls the key values into structured data. It reads parties, effective and expiration dates, governing law, dollar amounts, case numbers, and clause language. Because legal files arrive as scans, faxes, and image-only PDFs, OCR is the step that turns a stack of paper into data a legal team can search, review, and load into its systems.
OCR extracts data from legal documents in four steps: it captures the file from a scan or PDF, reads the text, finds each value next to its label or clause, and validates it. The engine pulls parties, dates, amounts, governing law, and key terms, then returns named fields and tables rather than a wall of text. Modern AI reads by understanding document structure, so it handles an unfamiliar contract layout without a fixed template.
Yes. AI reads a contract, locates each term next to its clause, and returns structured fields: the parties, effective and expiration dates, renewal and termination terms, governing law, payment amounts, and obligations. It works across MSAs, NDAs, leases, and statements of work without a template per contract type. High-confidence values pass straight through, and anything ambiguous routes to a reviewer, so a misread renewal date never slips into a matter on a guess.
Modern AI legal OCR commonly starts around 95% field-level accuracy on clean documents and climbs toward 99% with tuning and validation. Accuracy depends on scan quality, handwriting, and how dense the document is. The dependable pattern is straight-through processing for high-confidence values and a short human review queue for anything the engine flags, so a misread amount, date, or party name never posts to a legal file unchecked.
Reputable legal document processing software protects client-confidential files with encryption in transit and at rest, role-based access controls, detailed audit logs, configurable retention, and US-based data handling, often backed by a SOC 2 program. Those controls matter because legal documents carry privileged and sensitive information. Ask any vendor where data is stored, how long it is retained, who can access it, and whether processing can run without using your documents to train shared models.
Legal document processing software handles contracts and agreements, court filings and pleadings, discovery and exhibit sets, corporate and formation records, deeds, leases, and title documents, engagement letters, and legal invoices. A single matter can pass dozens of these among the firm, the client, opposing counsel, and the court, which is why classifying them automatically is the first step before any data gets extracted.
You extract data from a contract with AI that reads the agreement, finds each term next to its clause, and returns structured fields. It captures the parties, effective and expiration dates, renewal and notice periods, governing law, payment terms, and amounts. Because it reads by understanding layout and clause language rather than a fixed template, it handles MSAs, NDAs, leases, and amendments from any source, then validates the values before they reach your system.
Yes. OCR reads scanned court documents, including pleadings, motions, orders, and filed exhibits, and pulls the case number, court, parties, filing dates, and docket references into structured fields. Court files often arrive as low-quality scans or faxes, so the reliable approach pairs automatic extraction with a review queue for low-confidence reads, letting a litigation team index and search a case file instead of paging through PDFs by hand.
The best legal document processing software classifies a mixed matter file, reads printed and handwritten legal documents accurately, extracts the parties, dates, terms, and amounts your team relies on, validates them, and exports to your document management or contract system through an API. DocuOCR does this across contracts, court filings, discovery, corporate records, and legal invoices, and lets you test it on your own documents first.
Locate parties, dates, obligations, and clauses across contracts without reading each one.
How OCR turns a folder of signed PDFs into searchable, structured contract data.
The end-to-end IDP workflow that classifies, reads, extracts, and validates documents in one pipeline.
The full platform behind the legal workflow, with a dashboard for teams who want document data without code.
The focused tool for reading a single contract: parties, dates, terms, governing law, and amounts.
Pull every obligation, deadline, and clause out of signed contracts as structured, source-linked data for your CLM or obligation register.
Digitize a repository of signed contracts, extracting parties, dates, renewal terms, and clauses into structured records for your CLM.
How the engine sorts a mixed matter file by document type before extraction runs.
How DocuOCR reads structured legal forms and intake sheets, including hand-completed fields.
The developer endpoint that classifies, reads, and extracts legal documents inside your own app.
Upload a contract, pleading, or legal invoice, watch DocuOCR read it and pull out the data, then connect the API to process every matter file that follows on its own.
