The text discusses the limitations and challenges of current Optical Character Recognition (OCR) APIs, which are often restricted to solving a limited set of use cases and lack flexibility. These APIs struggle with processing custom data, require extreme post-processing, and have difficulties handling handwritten text, images with low resolution, and non-English languages. Despite these limitations, OCR technology can still be beneficial for businesses looking to automate data extraction and process automation, particularly in industries such as healthcare, finance, and logistics. The text also highlights the benefits of using Nanonets' pre-trained OCR API, which can handle a wide range of use cases, including images with varying contrast levels, font sizes, and angles, and supports 40+ global languages. Additionally, Nanonets offers a flexible and scalable solution that allows users to train their own models using a simple 9-step process.