What is OCR: definition and presentation

Last update:

May 9, 2025

5 minutes

Learn what OCR (Optical Character Recognition) is, how the technology works, and how it can transform paper or digital documents into actionable data. From finance to human resources to logistics, OCR is now finding concrete applications in many sectors. This article also explores the benefits of next-generation OCR solutions, powered by artificial intelligence, like Koncile.

We simply explain to you the essentials of OCR, its concrete uses and its advantages.

What is an OCR

What is OCR?

OCR means Optical Character Recognition. One OCR tool is a technology for converting text documents into input. This includes documents that are printed, handwritten, or scanned. OCR software analyzes the various visual components of these documents (PDF, images or scans, for example) and deduces the characters from them to reconstitute a machine-readable file, in the form of structured text.

How does OCR work?

An OCR system is based on this set of technologies:

Computer Vision: Computer vision to analyze the image and identify text shapes, lines, and characters.

Natural Language Processing: Natural language processing to understand the context of the text and its information of interest. For example, the system needs to understand that a string of characters is a date, name, or amount in the context of the document and how to respond accordingly.

The OCR process is generally as follows:

  • Image pre-treatments
  • Detecting text boxes
  • Character recognition
  • Creation of a structure of the extracted data such as a table, a form, or simply data in the form of JSON.

Some modern solutions such as new accounting software Koncile adds a layer of artificial intelligence for data validation, line-by-line context extraction, detection of errors, errors, inconsistencies, duplicates, or other anomalies.

What are the fields of application of OCR?

OCR is used in many sectors, with very varied use cases:

  • Finance & accounting : Extracting data on invoices, bank statements, order forms.
  • Human resources : automated analysis of resumes, employment contracts, pay slips.
  • Transport & Logistics : processing of delivery notes, CMR, waybills, maritime bills of lading.
  • realty : data extraction from sales agreements, status reports, reservation contracts.
  • Health : automated reading of prescriptions, care sheets, analysis results.
  • Retail : recognition of cash receipts and receipts for accounting integration or commercial analysis.

Thanks to modern OCRs, these once manual tasks are becoming automated, fast, and reliable, with a strong impact on productivity.

What are the benefits of OCR?

Using OCR in your business processes allows you to:

  • Save considerable time on manual entry
  • Drastically reduce human errors
  • Automatically standardize and structure data from various documents
  • Streamline document processing flows
  • Improve traceability and compliance (thanks to usable and historical extractions)
  • Decrease operational costs

In a professional context, an OCR makes it possible to transform an administrative burden into a lever for efficiency.

What is the difference between a classic OCR and an AI OCR?

Classic OCR is limited to detecting and converting plain text. It makes no contextual distinction, does not understand the extracted data, and cannot structure it accurately.

Conversely, an OCR powered by artificial intelligence (AI), like Koncile, is capable of:

  • Read complex documents line by line (invoices, tables, contracts...)
  • Understand titles, values, and their business meaning
  • Identify key fields automatically
  • Detect inconsistencies or anomalies
  • Adapt to different formats and structures without manual reconfiguration

AI OCR doesn't just extract: it interprets, controls, and values data.

How do I choose an OCR solution?

Before choosing OCR technology, ask yourself the right questions:

  • What types of documents should I process (PDFs, scans, forms, tables...)?
  • Do I need an API or a web interface?
  • Do I need to customize the fields to be extracted?
  • Is the volume of documents large or recurring?
  • Is my need only for extraction or also for control/structuring?
  • Do I need to integrate OCR with my existing tools (ERP, CRM, HRIS...)?

A good OCR solution should be:

✔️ Simple to integrate

✔️ Reliable on all types of documents

✔️ Customizable according to business needs

✔️ Scalable and AI-compatible

Jules Ratier

Co-fondateur at Koncile - Transform any document in structured data with LLM - jules@koncile.ai

Jules leads product development at Koncile, focusing on how to turn unstructured documents into business value.