Mistral has launched a new optical character recognition (OCR) application programming interface (API) called Mistral OCR. Amid the growing number of inference models, this API is specifically designed to deliver advanced document understanding capabilities.

Mistral OCR can extract content with high accuracy from unstructured PDF files and images, including handwritten notes, printed text, pictures, tables, and formulas, presenting the data in a structured format. Structured data refers to information organized in predefined ways, such as rows and columns, making it easier to search and analyze. Common examples of structured data include names, addresses, and financial transactions stored in databases or spreadsheets. In contrast, unstructured data lacks a specific format or organization, making it more challenging to process and analyze. Unstructured data encompasses a wide range of types, including emails, social media posts, videos, images, and audio files. Since unstructured data cannot be neatly incorporated into traditional databases, specialized tools and techniques like natural language processing (NLP) and machine learning (ML) are often used to extract valuable insights.

Mistral OCR supports multiple languages, offers fast processing speeds, and can integrate with large language models (LLMs) to enhance document comprehension. This is particularly significant for organizations looking to transform their documents into AI-ready formats. According to Mistral's blog post announcing the new API, 90% of all business information exists as unstructured data. As a result, this innovative API is expected to significantly assist organizations aiming to digitize and catalog their data for use in AI applications or internal/external knowledge bases.