DocuOCR reads every inbound document, works out what type it is, splits mixed batches into separate files, and routes each one to the right extraction path. No manual sorting, no keyword rules to maintain, and no template for every layout.
Built for US finance, operations, and healthcare teams that need documents sorted and their data captured at volume.
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Document classification software is the step that decides what each document is before anyone tries to use it. You feed it a stack of scans, PDFs, or emailed attachments, and it reads each page, recognizes whether the file is an invoice, a contract, a bank statement, a tax form, or an ID, and labels it. That label is what lets the rest of your workflow run on its own, because the system now knows which fields to pull and where each file should go.
Most inbound mail is messier than a clean one-document-per-file stack. A single scanned PDF often holds three different documents back to back, or a vendor sends an invoice with a remittance slip and a packing list stapled behind it. Classification software handles that too: it splits the batch at the right page boundaries, so each document becomes its own record instead of one jumbled file that a person has to pull apart by hand.
The difference between basic and intelligent classification matters in production. Rule-based tools match fixed keywords or a zone on the page, so a new vendor format or a reworded header quietly breaks them. AI classification reads the content and the layout together, so it sorts documents it has never seen and assigns a confidence score to every decision. Anything below your threshold goes to a quick human review instead of being filed wrong and discovered weeks later.
Read, classify, split, route. Set the categories once and documents sort themselves from then on.
OCR turns each scanned or photographed page into machine-readable text, so the classifier has both the words and the layout to work from.
AI weighs content, structure, and visual cues to decide the document type and assigns a confidence score to the call.
When one file holds several documents, DocuOCR finds the page boundaries and splits it into separate, correctly labeled records.
Each classified document flows to the right extraction path, and the structured fields export to your ERP, accounting, or content system.
# scan_batch_0915.pdf (6 pages) -> classified { "documents": [ { "type": "invoice", "pages": "1-2", "confidence": 0.99, "routed_to": "accounts_payable" }, { "type": "bank_statement", "pages": "3-5", "confidence": 0.97, "routed_to": "reconciliation" }, { "type": "w9_form", "pages": "6", "confidence": 0.95, "routed_to": "vendor_onboarding" } ] } # one batch, three documents, sorted
Real documents vary, so classification uses several signals at once instead of one brittle rule.
The model reads the actual text, the terms, totals, and phrasing, to tell an invoice from a contract even when both share a logo and a layout.
Visual cues like field positions, tables, and stamps help classify scanned or degraded pages where the text alone is incomplete.
Beyond the type, classification can flag what a document needs, such as a payment, a signature, or a review, so it routes to the right action.
Assign each file one category, or apply several tags when a document legitimately belongs to more than one class.
AI recognizes document types it was never explicitly trained on, so a new vendor format sorts correctly without you building a rule.
Detects where one document ends and the next begins inside a single scanned file and separates them into individual records.
Everything between a stack of unsorted files and clean, labeled data in your systems, handled without manual triage.
Incoming scans and emails get recognized and labeled automatically, so no one spends the morning deciding which pile each file belongs in.
Multi-document PDFs are split at the right boundaries into separate records, ending the manual job of pulling stapled scans apart.
Built-in OCR reads scanned, faxed, and photographed pages with no selectable text so image-only files can still be classified.
Every decision carries a confidence score, and anything below your threshold drops into a review queue instead of being filed wrong.
Each classified type flows to the right extraction path, then exports as JSON, Excel, or CSV into your ERP, accounting, or content system.
SOC 2, encryption in transit and at rest, and US data handling keep sensitive documents protected through the whole pipeline.
People mix these up constantly. Classification decides what a document is; extraction pulls the values out of it. They run in that order, and you need both.
| Factor | Document classification | Data extraction |
|---|---|---|
| Question it answers | What kind of document is this? | What values does it contain? |
| Output | A document type and label | Named fields and tables |
| Order in the pipeline | First step | Runs after classification |
| Example result | "invoice", pages 1 to 2 | invoice number, total, due date |
| Also handles | Splitting and routing batches | Validating each captured value |
| Without it | Files extracted with the wrong rules | Type known, but no usable data |
DocuOCR runs both in one pass. It classifies each document, routes it to the matching extraction model, and returns the type plus the structured fields together, so you never have to wire classification and extraction up as two separate tools.
Any team that receives a mix of document types and has to sort them before working on them is a fit.
Separate invoices from remittances and statements in the same mailbox, then route each to the right approval and posting flow.
Classify statements, applications, and KYC documents during onboarding so each goes to the correct lending or review queue.
Sort claims, EOBs, and intake forms, including hand-printed ones, and route validated records into claims and EHR systems.
Classify decades of mixed archive scans into searchable categories instead of one undifferentiated dump of PDFs.
Tell contracts, exhibits, and correspondence apart in large discovery sets so review starts with documents already grouped.
Classify bills of lading, packing lists, and purchase orders so each document type posts to the right system automatically.
Sort documents by hand in the dashboard, or call the same engine from your own app with one REST request. Post a file and get back the document type, the page split for multi-document files, a confidence score, and the extracted fields. No template setup and no per-vendor rules to maintain.
# classify and split a document with one call curl https://api.docuocr.com/v1/classify \ -H "Authorization: Bearer $KEY" \ -F "[email protected]" \ -F "split=true" # -> type + page split + confidence + fields
No seat licenses and no setup fees. Start free to check classification accuracy on your own documents, then pay per page as your volume grows. Higher volumes move to committed plans with lower per-page rates and priority throughput.
The questions people ask most before they choose document classification software.
Document classification software automatically identifies what type each document is and sorts it into the right category, such as invoice, contract, statement, or ID. It reads the page with OCR, recognizes the document by its content and layout, and routes it to the correct workflow so the right data gets extracted next, with no manual sorting by staff.
Document classification works by reading a document and matching its content and layout against learned categories. OCR turns the page into text, then an AI model weighs the words, structure, and visual cues to decide the document type and assign a confidence score. High-confidence files route automatically, and anything uncertain drops into a review queue for a person to confirm.
Classification decides what a document is; extraction pulls the values out of it. Classification answers "is this an invoice, a contract, or a statement?" and routes the file. Extraction then answers "what is the invoice number, total, and due date?" Classification comes first because you have to know the document type before you know which fields to capture.
Intelligent document classification uses AI to recognize a document without a separate rule or template for every layout. Older systems matched fixed keywords or zones and broke on any new format. Intelligent classification reads content and structure together, so it correctly sorts a vendor invoice or a form it has never seen, which is what holds up across real-world document variety.
Yes. OCR is the first step for any scanned, faxed, or photographed file, turning the image into machine-readable text so the classifier has something to read. The classification model then weighs that text alongside layout and visual features to decide the document type. On digital PDFs with selectable text, the model can classify directly without an OCR pass.
Automated document classification on common business documents typically reaches the high 90s in accuracy, often matching or beating manual sorting where people make 1 to 5 percent errors. Accuracy depends on document quality and how distinct the categories are. Good software returns a confidence score on every decision and sends low-confidence files to a review queue instead of guessing.
The best document classification software classifies common business documents accurately out of the box, splits mixed batches into separate files, scores its confidence, routes each document to the right extraction path, and exports to your systems. It should meet US security standards like SOC 2. DocuOCR does all of this and lets you trial it free on your own documents first.
Document classification software is usually priced per page or per document rather than per seat, so the cost tracks volume instead of headcount. DocuOCR starts free so you can test classification accuracy on your own documents, then charges per page as you scale, with lower rates on committed plans. There are no setup fees and no per-user licenses.
How classification, capture, extraction, and validation fit together in one end-to-end IDP workflow.
Ingest documents from scanners, email, and an API, then classify and extract them in the same pass.
The full platform behind classification, with a dashboard for teams who want document data without code.
Turn each classified document into structured JSON, Excel, or CSV with named fields and intact tables.
Put sorting and keying on autopilot so document data flows into your ERP or CRM without manual work.
The developer endpoint that classifies and extracts documents into structured JSON inside your own app.
Upload a document, watch DocuOCR recognize its type and pull out its data, then connect the API to classify and route every file that follows on its own.
