---
title: "OCR | Skills We Assign For | Azendo"
description: "OCR in document pipelines — accuracy, preprocessing, confidence, plus the Azendo roles assigned for it."
url: "https://azendo.co/skills/ocr/"
---

[Skills](https://azendo.co/skills/) Automation platforms 

# OCR.

Optical character recognition extracts text from images and scanned documents. Accuracy depends heavily on input quality, and the realistic output is text with errors rather than a perfect transcription.

## Where OCR fits on a long engagement.

Input quality dominates everything else. A clean digital PDF extracts perfectly; a photographed document at an angle in poor light produces errors no engine eliminates. Preprocessing — deskewing, contrast correction, denoising — frequently improves results more than changing OCR engine does.

Confidence scores are the output people ignore and should not. An engine reporting low confidence on a field is telling you something useful, and routing those to human review rather than accepting them silently is what makes a document pipeline trustworthy.

## What an assigned team does with OCR.

Accuracy expectations need setting honestly at the start. Ninety-five percent character accuracy sounds excellent and means several errors per page, which for financial data is not acceptable without verification.

Being clear about that before a process is designed around it prevents a predictable disappointment, and it is part of scoping as described in [how an assignment runs](https://azendo.co/how-it-works/).

## What we use OCR for.

* Preprocessing before recognition Deskew and contrast correction, which often helps more than a different engine.
* Low-confidence fields routed to review The engine's own uncertainty used rather than discarded.
* Accuracy expectations set honestly What the error rate means in practice, stated before a process depends on it.

## How OCR capacity is assigned.

Document extraction is assigned inside automation capacity, with realistic accuracy stated before the surrounding process is designed.

## Roles we assign OCR for

* [RPA Developer AI automation engineering](https://azendo.co/services/ai-automation-engineering/rpa-developer/)

## Service lines it sits in

* [AI automation engineering](https://azendo.co/services/ai-automation-engineering/)

Capacity is agreed as a committed monthly capacity across a discipline, not per skill.

## Related in automation platforms

* [Zapier — skill we assign for](https://azendo.co/skills/zapier/)
* [Power Automate — skill we assign for](https://azendo.co/skills/power-automate/)
* [UiPath — skill we assign for](https://azendo.co/skills/uipath/)
* [Automation Anywhere — skill we assign for](https://azendo.co/skills/automation-anywhere/)
* [Blue Prism — skill we assign for](https://azendo.co/skills/blue-prism/)
* [Workato — skill we assign for](https://azendo.co/skills/workato/)
* [MuleSoft — skill we assign for](https://azendo.co/skills/mulesoft/)
* [Boomi — skill we assign for](https://azendo.co/skills/boomi/)

## Tell us what your roadmap needs OCR for.

A service delivery manager replies with the disciplines we would assign, the monthly capacity and what the first month looks like.

[All skills we assign for](https://azendo.co/skills/)