If you've landed here, chances are you're exploring smarter alternatives to OCR for document data extraction. Let's dive into how Augmend compares—and when it might be a right solution for you.
What is Optical Character Recognition or OCR
OCR is the workhorse technique for extracting text from scanned documents and images. This relatively mature technology is now offered as a service by almost all major software vendors such as AWS, Google, Microsoft and IBM.
Classical OCR technique has been fine-tuned over a number of years for digitizing documents, i.e., converting scanned text into searchable text. OCR is used across industries in a variety of applications, for example process of loan applications, health records, package labels. Chances are your organization already uses it to process invoices or receipts.
What are the limitations of OCR
Despite its ubiquity, OCR has its limitations, for example:
- • extracting from complex tables is tricky,
- • image and visual context are ignored as OCR is strictly text-centric
- • Subtle variations in formatting or handwritten notes can throw off extraction accuracy
Consider an example receipt below:
A typical OCR engine is likely to extract $30.24 as the TOTAL and completely miss the handwritten tip. This can only be avoided, if custom rules have been programmed to catch such deviations. But anticipating every deviations is impossible.
How LLMs can help
On the other hand, LLM with the right input will have no problem handling such deviations and will correctly infer that the total amount paid is actually $35.24. So even with pure text, LLM can outperform OCR. And with their human-like abilities in reading complex tables and interpreting images data they do things that OCR simply cannot.
While some OCR tools now integrate LLMs, these hybrid systems often require fine-tuning and are optimized for narrow use cases with limited field extraction
Why Augmend might be a good OCR alternative?
Augmend goes beyond OCR and beyond basic LLM wrappers. Here is how it stands out:
- • Advanced LLM Integration: It uses state of art LLM algorithms to extract data but it is not just a wrapper on the LLM model
- • Multi-language Support: Can handle almost all major languages and translate them in one go thanks to the power of LLM technology
- • High-volume Extraction: Can extract even 50-100 fields in one go, by injecting the right domain knowledge
- • Easy Configuration: Is easily configurable, so it can work on a variety of use cases (e.g., quality, procurement, innovation and marketing) with quick adjustments
- • Format Flexibility: Handles extreme variations in incoming document formats, for example, one document has tables whereas another has only text blobs
- • Visual Intelligence: Is really effective in handling pictures and extracting interpretative information from them
- • Data Validation: Produces validated data to guarantee that the data output is in the right format and is free from hallucinations. It errs on the conservative side, rather not produce any output than produce wrong output.
So, with Augmend you have intelligent document processing at your fingertips. Unlike OCR's text-centric approach, Augmend provides intelligent document processing that adapts to various formats and delivers structured, reliable data for enterprise systems.
Augmend is built for both engineers and non-technical users
Furthermore, Augmend is simple to use for non-technical users too. Such users simply need to upload the files they want processed and download their data that they can collect and analyse in Excel should they want to. We are also building API capabilities keeping in mind our advanced users and this capability will be live soon.
Do you want to see Augmend in action?
If you're exploring OCR alternatives or smarter data extraction tools, Augmend might be the solution you've been waiting for. Click the button in the navigation bar to book a demo or consultation today.