Modern companies are increasingly implementing artificial intelligence to automate routine operations. One of the key areas of such automation is intelligent document processing – a technology that allows AI systems to recognize, extract and interpret data from various digital documents. The Businessware Technologies platform presents a regularly updated benchmark – an objective assessment and comparison of the capabilities of AI models used in IDP tasks.
What is it and what should you pay attention to?
Testing of AI invoice processing is carried out on real data sets, including documents in different languages, with different structures and formats. Such sets reflect the conditions that enterprises face in their daily work – be it invoices, tables, forms or commercial offers. The key evaluation parameters are:
- recognition accuracy;
- processing time and cost of the models.
Particular attention is paid to how effectively language models such as GPT-4o, Gemini 2.5 Pro, Amazon Textract, as well as services from Microsoft and Google, cope with documents containing tables, complex structures, and multi-level text blocks. For example, in June 2025, researchers compared the performance of models for data extraction from tables, and in March, the focus shifted to processing invoices and commercial documents.
Each monthly report published by Businessware Technologies provides an in-depth analysis, reflecting both basic metrics and additional features of each model. This allows businesses to make informed decisions when choosing tools for IDP, understanding which AI is best suited for specific tasks.
Thus, the platform not only demonstrates the technical capabilities of leading models, but also forms benchmarks in the field of enterprise AI. Thanks to such research, IDP becomes a more predictable and accessible solution for companies striving for digital transformation. In addition, analytics from Businessware Technologies helps to identify weaknesses in current solutions and suggests areas for their improvement. Such tests are especially useful for developers, integrators and business analysts planning to implement AI in document flow. Thanks to regular comparative reports, it is possible to track the dynamics of technology development and adapt automation strategies to current market opportunities.
