Category

OCR Software

Software that turns scanned documents, PDFs and photos of paper into structured, searchable data — for teams drowning in manual data entry from invoices, forms and receipts.

4 businesses

Nanonets

San Francisco, California, United States

Nanonets agents understand key details in files - like invoices, pos, bol & clinical documents - work through complex processes…

4.9 55 reviews

Octoparse

Irvine, California, United States

Octopus data inc. Is a software company specialized in collecting data from both static and dynamic websites. Octoparse is a…

4.5 9 reviews Usage-based

Infrrd

San Jose, California, United States

At infrrd, we help businesses handle messy, unstructured documents. Our AI-powered platform extracts, organizes, and automates…

4.4 5 reviews

Mobile Deposit

San Diego, California, United States

Mitek protects what’s real across digital interactions in a world of evolving threats. Mitek helps businesses verify identities…

4.1 Per user

Businesses in this category build and sell software that reads text and data out of documents — scanned invoices, PDFs, forms, receipts, ID cards, contracts, even photos taken on a phone — and turns it into data you can actually use: fields in a database, rows in a spreadsheet, records in an ERP or accounting system. The work they're hired to do ranges from a simple API that converts an image to plain text, through to systems that recognise specific fields on an invoice (vendor, PO number, line items, totals) and push them straight into a payables workflow without anyone retyping anything.

People end up looking for this when paper, or paper masquerading as PDF, has become a bottleneck. An accounts payable team is keying in hundreds of supplier invoices a week by hand. A back office is retyping figures from bank statements or expense receipts into a finance system. A records team has boxes of scanned contracts or forms that are unsearchable and unusable for anything beyond storage. Growth has outpaced the manual process that used to just about cope, and the cost shows up as backlog, data entry errors, slow month-end close, or staff spending their day on typing rather than on the work the business actually needs from them.

The providers here solve this in different ways, and the differences matter when you're choosing between them. Some are narrow, fast OCR engines or SDKs meant to be embedded into another product; others are full intelligent document processing platforms with machine learning models trained to find fields on messy, inconsistent document layouts without a template, plus a human-review step for anything the model isn't confident about. Some specialise by document type — invoices and accounts payable, receipts and expenses, ID and compliance documents — and are tuned accordingly; others are general-purpose and expect you to configure or train them.

Worth comparing: accuracy on your actual document types (a demo on clean invoices tells you little about your supplier's crumpled scans), whether it needs templates per document layout or handles variation out of the box, how review and correction of low-confidence extractions is handled, deployment options (cloud API versus on-premise, which matters if you're bound by data residency or compliance rules), how it integrates with your existing accounting or ERP system, and pricing — usually per page or per document, which adds up fast at volume.

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