What Is Document Capture Software? How Modern Tools Digitize and Extract Your Data

Document capture software digitizes paper documents and extracts data from both physical and digital files, converting unstructured information into structured, usable data. It goes beyond simple scanning — modern capture tools ingest documents from any source (email, upload, scan, mobile photo) and pull out the specific fields your business needs. If your team still manually reads invoices, purchase orders, or bills to type data into a spreadsheet or system, document capture software is the category built to replace that work.

Lido is AI-powered document capture software that handles both ingestion and extraction from any source — email, scan, upload, any format — without templates. Instead of building rules for every document layout, Lido’s AI reads and understands documents the way a person would, pulling out the data fields you need regardless of format. Companies like ACS Industries, Esprigas, and Hocutt use Lido to process thousands of documents monthly across wildly different formats, all without manual data entry.

How document capture software works

Document capture follows a five-stage pipeline: input, digitization, recognition, extraction, and export. Every document you process moves through these stages, whether it arrives as a paper invoice or a PDF attachment in your inbox.

1. Input. Documents enter the system from multiple sources — scanners, email inboxes, file uploads, mobile cameras, cloud storage folders, even fax-to-digital converters. Modern capture software treats all of these as equal entry points. The days of walking to a scanner are mostly over; for most businesses, the primary input channel is now email.
2. Digitization. If the document is physical (scanned or photographed), this stage converts it to a digital image. For documents that are already digital — PDFs, spreadsheets, Word files — this step is essentially skipped. The key point: digitization turns paper into pixels, but it doesn’t yet understand what’s on the page.
3. Recognition. OCR (optical character recognition) and AI read the content on the page. Traditional OCR converts image-based text into machine-readable characters. AI-powered recognition goes further, understanding the layout, identifying where headers, line items, totals, and other fields sit on the page, even when every document looks different.
4. Extraction. This is where document capture earns its value. The software pulls structured data fields — vendor name, invoice number, line item descriptions, amounts, dates — from the recognized content. Template-based tools need pre-built maps for each layout. AI-powered tools like Lido extract fields from any layout without setup.
5. Export. Extracted data flows to your destination system: an ERP, accounting software, a spreadsheet, a database, or an API endpoint. The document itself may also be stored or routed for approval. The goal is that data arrives where your team needs it, already structured, without anyone retyping it.

What’s changed most in this pipeline isn’t any single stage — it’s that modern capture is less about scanning paper and more about ingesting documents from every digital channel where they arrive.

Why businesses still struggle with document capture

The core problem isn’t capturing the document image — it’s extracting usable data from it. Most organizations solved the “going paperless” challenge years ago. What they haven’t solved is what happens after a document is digital.

1. Documents arrive in too many formats and channels. A single vendor might send invoices as PDF attachments one month, embedded in the email body the next, and as an Excel file the month after that. Multiply this across dozens or hundreds of vendors, and the format variety becomes unmanageable with rigid tools.
2. Existing tools require format-specific setup. Many capture solutions need you to build a template or mapping for each document layout. That works when you process one type of document from one source. It breaks down when you handle purchase orders from fifty different customers or utility bills from thirty different providers.
3. Volume spikes overwhelm manual processes. Teams that “get by” with manual data entry at 200 documents a month hit a wall at 2,000. Hiring more people to type data doesn’t scale, and the error rate climbs as the work gets more repetitive.
4. Data quality degrades at scale. Manual keying introduces typos, transposed numbers, and missed fields. These errors compound downstream — a wrong invoice amount becomes a payment discrepancy, which becomes a vendor dispute, which takes hours to resolve.
5. Different departments have different document types. Accounts payable handles invoices. Operations handles bills of lading and waybills. Procurement handles purchase orders. Each team has its own capture needs, and few tools handle all of them without separate configurations.

Document capture software vs. document management systems

This is one of the most common points of confusion. Document capture and document management solve fundamentally different problems, and buying the wrong one wastes both money and time.

1. Document management systems (DMS) — tools like SharePoint, Box, Google Drive, and Dropbox — store and organize documents. They handle search and retrieval, version control, access permissions, and collaboration. A DMS answers the question: “Where is my document?”
2. Document capture software extracts DATA from documents. It converts unstructured content (a PDF invoice, a scanned receipt, an emailed purchase order) into structured fields you can use in other systems. Document capture answers the question: “What’s IN my document?”

Many teams buy a DMS expecting it to solve their data extraction problem. They end up with perfectly organized folders full of invoices — but someone still has to open each one and manually type the data into their accounting system. A DMS makes documents findable. Document capture makes documents usable.

The two are complementary, not interchangeable. The ideal workflow uses capture to extract data and a DMS to archive the source document. But if your bottleneck is manual data entry, a DMS alone won’t fix it.

What to look for in document capture software

Not all capture tools are built the same. The features that matter most depend on your document volume, variety, and where your data needs to end up. Here are the capabilities that separate modern solutions from legacy ones.

1. Multi-channel ingestion. Your software should accept documents from email, file upload, scanner, mobile camera, and cloud storage without requiring different workflows for each. If your team has to manually download an attachment, save it to a folder, then upload it to the capture tool, you’re adding friction that defeats the purpose.
2. Format flexibility. PDFs, images (JPG, PNG, TIFF), spreadsheets, Word documents, and even plain email text should all be processable. The tool shouldn’t force you to convert files to a specific format before processing.
3. Template-free extraction. This is the dividing line between older and modern capture tools. Template-based systems require you to define where data fields appear on each document layout. Template-free, AI-powered systems read and understand documents regardless of layout — the same way a person would.
4. Field-level accuracy. Extracting data is only valuable if the data is correct. Look for tools that provide confidence scores, flag uncertain extractions for review, and let you correct errors in a way that improves future accuracy.
5. Batch processing. If you receive dozens or hundreds of documents at once (end-of-month invoice batches, for example), the software should handle bulk processing without you feeding documents one at a time.
6. Integration with downstream systems. Extracted data needs to flow somewhere — your ERP, accounting software, spreadsheet, or database. Native integrations, API access, or direct export to tools like Excel and Google Sheets are essential.
7. Mobile capture. Field teams, delivery drivers, and warehouse staff often need to capture documents on the spot. A mobile-friendly interface or camera capture option extends your capture workflow beyond the desktop.
8. Setup time. Legacy tools can take weeks or months to configure with templates and rules. Modern AI-powered capture tools should get you extracting data in hours, not weeks. If a vendor tells you implementation takes a quarter, that’s a signal the tool isn’t truly intelligent.

How document capture has evolved from scanning to AI extraction

Document capture has gone through three distinct generations, each solving a different version of the problem. Understanding this evolution explains why many organizations are still stuck with tools built for an earlier era.

First generation: physical scanners and basic OCR (1990s–2000s). The original problem was simple — paper everywhere, and businesses needed digital copies. Flatbed scanners and basic OCR turned paper into searchable PDFs. The goal was going paperless, and success meant having a digital file instead of a paper one. Extraction was minimal; you might get full-text search, but pulling specific data fields still required human eyes.

Second generation: template-based capture (2010s). As documents went digital-first (PDFs sent via email instead of paper sent via mail), the problem shifted from “digitize the paper” to “extract the data.” Template-based tools let you map fields on a document layout: “the invoice number is always in this corner, the total is always on the last line.” This worked well for standardized documents from a single source, but broke down with format variety. Every new vendor layout required a new template.

Third generation: AI-powered capture (2020s). Building on advances in intelligent document processing, AI-powered tools understand documents without pre-built templates. They recognize that a field labeled “Invoice #,” “Inv No.,” or “Bill Number” all mean the same thing. They handle layout variations, multi-page documents, and mixed formats without setup. The shift from “digitize the paper” to “extract the data” is the key evolution — and it’s what makes modern capture tools fundamentally different from their predecessors.

Most businesses today operate somewhere between the second and third generation. They’ve gone paperless, but they’re still manually extracting data or maintaining brittle template libraries. The jump to AI-powered capture eliminates that maintenance entirely.

How Lido captures and extracts data from any document

Lido handles the full capture pipeline — ingestion from any source, recognition, extraction, and export — without templates, rules, or format-specific setup. Here’s how real companies use it.

ACS Industries: purchase orders from every format imaginable. ACS Industries receives purchase orders via email in every format — PDFs, spreadsheets, images, and plain email text. Before Lido, someone had to open each one, read it, and manually enter the order details. With Lido, all incoming POs are captured and extracted automatically, regardless of format. No templates. No per-vendor configuration. The same system handles a structured Excel PO and a hand-typed email with equal accuracy.

Esprigas: 27,000 documents a month via email auto-forwarding. Esprigas auto-forwards invoices from their email inbox directly to Lido. The system processes 27,000 documents monthly — reading each invoice, extracting vendor details, line items, amounts, and dates, then exporting the structured data to their downstream systems. The entire invoice processing workflow runs without manual intervention.

Hocutt: utility bills from dozens of different providers. Hocutt manages utility bills from dozens of providers, each with a completely different bill layout. Traditional capture tools would require a separate template for every utility company. Lido’s AI reads and extracts data from all of them with a single setup — the same extraction works whether the bill comes from a large national provider or a small municipal utility.

What these use cases share is format variety. The documents don’t look alike, don’t come from the same source, and don’t follow the same layout. That’s precisely where template-free, AI-powered capture delivers the most value.