Beyond Basic OCR: What Developers Really Need

Optical character recognition (OCR) is in every cloud platform and AI solution today—or so the vendors would like you to believe. The technology, after all, isn’t new. Since the 1970s, OCR has been used to digitize books and printed forms. Today, it’s marketed as a built-in feature in everything from scanners to automation tools.

But modern document processing is a different beast. Real-world use cases demand OCR that can handle handwriting, tables, multi-language text, and messy, unstructured scans. AI has taken OCR to new heights, yet not all solutions can keep the promises they make.

The developer’s guide to picking the right OCR

For developers, the differences between OCR solutions really matter. Choosing the wrong one means hours spent debugging edge cases, writing custom fixes, or manually cleaning up bad output.

The right OCR, on the other hand, delivers clean, structured results you can trust, freeing you up to focus on building features and scaling your product or automation workflow. Here are the features to look for:

1. Flexibility and support for complex documents
   

   Real business documents are messy. Charts, multi-column layouts, scanned forms, and scribbled invoices are all fair game. If your OCR can’t make sense of that structure, you’re left cleaning up the output by hand. That defeats the whole point of automation. Look for an option trained to handle these complexities so you get cleaner data at the get-go and fewer headaches down the line.

2. Accuracy and performance
   

   Even small data extraction errors can trigger compliance issues or force costly manual fixes. To be worth the investment, your OCR needs to deliver consistent reliability and precision. In practice, that usually means leaning toward commercial solutions, which are continuously updated and better supported—and away from open-source tools, which often struggle with handwriting, rotated text, or complex layouts.

3. Long-term reliability
   

   Reliability isn’t just about how well an OCR solution works today, but about whether it keeps working tomorrow. For long-term projects, choose a solution that’s actively maintained and continuously improved—typically by commercial OCR vendors. Open-source tools can be risky, since critical fixes or upgrades might never come. If business-critical automation flows come to a production stop, you don’t want to be left alone trying to fix it.

4. Tailor-made for the task
   

   General-purpose AI tools—like GPT-4.5—might seem like they can do it all, but they’re not reliable for core OCR tasks. Large language models (LLMs) can skip important content, hallucinate data, and do not deliver consistent results—and are also slower and more expensive to run than purpose-built OCR.

5. Developer support and documentation
   

   Quality software development kits (SDKs), well-documented APIs, clear guides—and, ideally, a sandbox or trial environment—go a long way in letting you speed up development without jumping through hoops. And once you're live, access to responsive technical support and an active developer community is a big help.

6. Predictable, scalable pricing
   

   Make sure you consider the complete, long-term cost of your OCR solution. Some options may look cheap upfront but get expensive fast when every feature is priced separately. Choose a provider with transparent, pay-as-you-go pricing that scales with your needs.

The all-in-one solution: ABBYY’s Document AI API

Despite the flood of OCR options out there, finding one that checks all the right boxes is still surprisingly hard. That’s why we built ABBYY’s Document AI API: a next-gen OCR service that goes far beyond basic text recognition.

At its core, ABBYY’s API extracts text. But it’s also part of a smarter document processing platform that adds structure, context, and intelligence to that raw output. Here’s what sets it apart:

• Purpose-built for document processing: Unlike tools that try to do everything, ABBYY’s API is built to do one thing really well: process real-world documents quickly and precisely. Be it invoices, contracts, forms, IDs, or whatever other format you’re working with, ABBYY Document AI API handles them cleanly without requiring hacks or workarounds. Plus, with built-in multilingual support, it’s ready for global use.
• Over 90% extraction accuracy: Precision is essential for business-critical workflows like Know Your Customer (KYC) in finance or customs clearance in logistics. Unlike LLMs or open-source tools that can hallucinate or break under pressure, ABBYY is built to deliver reliable results in these high-stakes use cases.
• Developer-friendly integration: ABBYY makes it easy to build, test, and ship fast with intuitive APIs, solid SDKs, and clear documentation. A self-service sandbox lets you get hands-on quickly, and structured outputs like JSON or HTML plug straight into your stack. Backed by decades of OCR expertise, ABBYY also gives you the support, community, and trust that come from successful, award-winning innovation.
• Fast setup and easy scaling: ABBYY’s pre-trained models for common business documents help you get started fast and connect with automation tools, AI models, or custom data pipelines. ABBYY is also cloud-native and made for high-volume document processing, so you can go from proof-of-concept to production fast with consistent performance and predictable pay-as-you-go pricing.

See what ABBYY can do

Choosing the right OCR solution comes down to what your work demands: accuracy, scalability, affordability, and dependable developer support. ABBYY’s new Document AI API checks every box. Plus, this technology is simply more consistent and precise than its competitors. If you need serious document processing, it’s the tool to trust.

If you’d like to give ABBYY’s API a try, join the waitlist to access our technical preview. See firsthand how ABBYY’s API makes document processing smarter, faster, and a whole lot easier.