Did you know businesses lose countless hours manually inputting data? Could OCR be your solution?

OCR technology can convert scanned documents and images into machine-readable text, this is useful for automation and analytics. But choosing the right service is essential. Not all OCR services are created equal. Let's talk about that.

This blog is your comprehensive guide to understanding and choosing OCR services, comparing top commercial vendors AWS, Google Cloud, and Azure

Let’s dive into it, picture this: a business gets hundreds of invoices every day. Right now, they've got people whose whole job is to read these papers and type the details into an Excel sheet. It's slow, and yeah, mistakes happen. Now, what if a computer program could read these invoices for them? That's where OCR comes in. It can pull out important stuff like the invoice number, the date, payment-related values, TINs (Tax identification numbers), etc. But here's the thing: not all invoices are easy to read. Some are handwritten, not all of them are in the same format, and some are in different languages. So, picking the right OCR tool is important to ensure everything runs smoothly.

Several commercial options stand out, notably AWS Textract, Google Cloud Vision, and Azure Computer Vision. These services come from three major cloud providers and offer a blend of ease and functionality. They're user-friendly and can easily fit into your existing workflow. All three have robust APIs and SDKs, so you can use them in various programming environments,and integrate smoothly into existing workflows, often requiring just a few lines of code to get started. But they're not all the same.

While the core objective of these services—text extraction—is the same, it's worth noting that while they all aim to solve the same problem, some may outperform others depending on the specific challenges you're looking to address. Whether it's pricing or accuracy, each service has its strengths and weaknesses, which we will delve into in the following section.

 Pricing Details (Last Updated: 03/09/2022)

Each of the three options has a similar price point, though Azure edges out as the most budget-friendly by a narrow margin. Therefore, it's crucial to understand the scale of your operations when making a selection, particularly if you're looking to optimise your consumption of resources

You should note that these costs are just for the basic OCR variants of these APIs, and each of the 3 solves other use cases that might be priced separately. For example, I really like Textract’s additional features like form and table analysis, but its important to consider that these specialised services cost more. It still makes sense if you need a ready black-box solution that is simple to integrate.

Accuracy

There is a lot of good material on which service performs better and for which use case Keep two things in mind: how accurate the service is and how off it can be when it makes a mistake. For this article, I looked at research by Curvestone. After you read this, you should check out their blog post. It's linked below and in the article, and it talks about how they figured out the accuracy of these services.

TL;DR while looking at these 3 services, Amazon Textract does a bit better with messy, scanned papers. It's good at figuring out the words and where they are on the page. But if your papers are clean and easy toread, all the services are pretty much the same. In such cases, considerations like the broader cloud platform offerings and cost structure should take precedence.

How to Pick the Right OCR Service for You

The "best" OCR service for you depends on what you're looking to do. Are you dealing with a lot of documents? What kind of documents are they?

Some Situations you may find yourself in:

Situation 1: High Volume and High Accuracy

• Example: Big hospitals with lots of health records
• Problem: Hospitals have tons of papers every day, like doctor's notes and test results. They need to be turned into digital files and they need to be right.
• What to Look For: You'll want a service that can handle a lot of records fast and without mistakes. A mistake can be a big deal here.
• Good Choices: Somethinglike AWS Textract or Google Cloud Vision. They're good at reading both typedand handwritten stuff. And it might be worth it paying a little extra for the added accuracy

Situation 2: High Volume and accuracy is not the main concern

• Example: A company that wants to know what people are saying in social media pictures and videos
• Problem: The company needs to go through a lot of data, but it doesn't have to be 100% right.
• What to Look For: You need something that can handle a lot of data. It  doesn't have to be perfect.
• Good  Choices: Azure Computer Vision could be a good fit as it is the cheapest. You could also use acheaper, open-source tool if your team has the know-how to train and develop these programs themselves.

I haven’t considered examples with low volume, but it's essential to note that the payoff from commercial OCR solutions reduces as the scale decreases. For smaller-scale tasks, there are numerous free open-source tools available. If your team possesses the skills and expertise, these tools can be a viable option. Options to check out include Tesseract, GOCR, and others.

 Key Takeaways:

1. OCR is a Game-Changer: If you're still manually inputting data from invoices or other documents, OCR can save you time, money, and a whole lot of headaches. It's like having a super-fast, super-accurate typist on your team.
2. Big Names in the Game: AWS Textract, Google Cloud Vision, and Azure Computer Vision are the big players here. They're reliable, easy to integrate, and each has its own set of perks. But remember, they're not one-size-fits-all.
3. Pricing  Matters: All three services are in the same ballpark when it comes to cost, but Azure is a smidge cheaper. If you're counting pennies, this could be your go-to.
4. Accuracy is Key: Amazon Textract shines when the going gets tough—like with messy, handwritten stuff. But if your documents are neat and tidy, any of the big three will do the job well.
5. Open-Source  Options: If you're on a budget or just love tinkering, there are open-source options like Tesseract and GOCR. They might not be as polished as the big names, but they can still get the job done.
6. Know Your Needs: Whether you're a hospital drowning in paperwork or a small business just looking to digitize business cards, there's an OCR solution that fits your needs. Make sure you pick the one that's right for your specific situation.

The world of OCR is always evolving, thanks to advancements in tech like deep learning. So, keep an eyeout for updates that could make your chosen service even better.

If you’re still confused? Don't sweat it. Reach out for a free consultation on how to go about digitally transforming your operations. Doing things right from Day 1 is easier than you think it is.

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References:

1. Curvestone's OCR Comparison: A deep dive into the accuracy of OCR services from Microsoft Azure, AWS, and Google Cloud. A must-read for anyone looking to understand the nitty-gritty of OCR performance. Read more
2. How to Compare OCR Tools: An article by Federico Ricciuti that compares various OCR tools, including Tesseract OCR, Amazon Textract, Azure OCR, and Google OCR. Great for those who want a broad view of available options. Read more
3. Google Cloud Vision Pricing: The official pricing page for Google Cloud Vision. Useful for anyone budgeting for an OCR project. Read more
4. AWS Textract: The official page for Amazon's Textract service. It provides detailed information on features and pricing. Read more
5. Azure Computer Vision: Microsoft's official page for Azure Computer Vision, detailing its features and pricing. Read more
6. IBM's Take on OCR: A blog post from IBM discussing the broader applications and implications of optical character recognition technology. Read more

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