Document Automation
Document automation uses OCR and intelligent processing to extract, classify, and digitize information from both physical and digital documents. We benchmarked various OCR solutions for accuracy and efficiency alongside intelligent document processing platforms, and examined whether LLMs outperform OCR tools in document automation.
OCR Accuracy Benchmark
We benchmarked leading OCR services across different document types: Printed text: All solutions achieve >95% accuracy. Printed media: 60-90% accuracy range. Handwriting: 20-96% accuracy range. Multimodal LLMs perform best, followed by cloud OCR services.
Agentic Document Extraction Benchmark
To identify the best agentic document extraction tool, we used 60 images, 30 of which display flowcharts of varying complexity. These flowcharts are uploaded as PNG images. We evaluated performance using node accuracy, edge accuracy, and decision accuracy. The second part contains 30 PNG images with tables from industry documents; the processing method is the same as for the flowcharts. The scoring metrics for this dataset include title accuracy, header accuracy, row accuracy, and cell accuracy.
Invoice Data Extraction Benchmark
To benchmark LLMs and OCRs in invoice data extraction, we used more than 400 key value pairs from 20 publicly available invoice samples, with various sizes and resolutions.
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Explore Document Automation
Invoice OCR Benchmark: Extraction Accuracy of LLMs vs OCRs
Invoice processing is a critical yet labor-intensive business operation that traditionally requires manual data extraction and entry into accounting systems. This manual approach is time-consuming and susceptible to human error.
Receipt OCR Benchmark with LLMs in 2025
Extracting data from receipts is essential for businesses since millions of employees are submitting their work related expenses via receipts. With the latest developments in generative AI and large language models, data extraction accuracy has reached approximately human levels. Benchmark results We used Claude 3.
Blackbaud AP Automation: 5 Software & Features Analyzed
Blackbaud offers accounting software, namely Financial Edge NXT. The product offers services in accounting such as: Although Financial Edge offers a wide range of solutions in the field of accounting, it can be improved with native software add-ons like Pairsoft for AP automation.
14 Rossum AI Alternatives / Competitors in 2025
Document processing is crucial in many industries such as finance automation and accounts payable. Alongside accounts payable AI (APAI) solutions, AI-driven Intelligent Document Processing (IDP) vendors such as Rossum capture attention. In this vibrant market, AP AI market spending is projected to surge to $1.9 billion by the end of 2025.
Top 10 Tungsten Automation (Kofax) Alternatives in 2025
With the acceleration of artificial intelligence (AI), businesses are constantly looking for tools to: Intelligent document processing (IDP) tools can do all this, and more. For this reason, the global Intelligent Document Processing (IDC) market sizeis expected to grow from USD 1.1 billion in 2022 to USD 5.
OCR Benchmark: Text Extraction / Capture Accuracy [2025]
OCR accuracy is critical for many document processing tasks and SOTA multi-modal LLMs are now offering an alternative to OCR. We tested leading OCR services to identify their accuracy levels in different document types: 2025 OCR benchmark results Product names were shortened above, their full names are listed below.
10 AP AI Applications in Accounts Payable Processes [2025]
We’ve written about accounts payable automation and invoice automation before, where we highlighted that AP processes can be mostly automated and shared criteria to select the right vendor.
State of OCR in 2025: Is it dead or a solved problem?
Optical Character Recognition (OCR) is one of the earliest areas of artificial intelligence research. Today OCR is a relatively mature technology and it is not even called AI anymore which is a good example of Pulitzer Prize winner Douglas Hofstadter’s quote: AI is whatever hasn’t been done yet.
Handwriting Recognition Benchmark: LLMs vs OCRs in 2025
Today, OCR technology provides higher than 99% accuracy with typed characters in high-quality images. However, the diversity in human writing types, spacing differences, and handwriting irregularities cause less accurate character recognition, as shown in the featured image. Thus, tools that read handwriting cannot provide the same accuracy that OCR systems offer on typed characters.