Recently, Mistral, a French developer of large language models (LLMs), introduced a new API designed to simplify the processing of complex PDF documents for developers. The Mistral OCR API utilizes optical character recognition to convert PDFs into text files, making them more accessible for AI models to analyze.
Large language models, which power popular tools such as OpenAI’s ChatGPT, are optimized for raw text input. As a result, companies seeking to integrate AI workflows recognize the importance of storing and indexing data in a clean, reusable format for AI processing.
Unlike other OCR APIs, Mistral OCR boasts multimodal capabilities, allowing it to detect and separate illustrations and photos from text blocks, and include them in the output with bounding boxes.
Moreover, the API formats its output in Markdown, a syntax used by developers to add formatting elements like links, headers, and bold text to plain text files, rather than producing a plain text wall.
Large language models heavily rely on Markdown for their training datasets. Similarly, AI assistants like Mistral’s Le Chat and OpenAI’s ChatGPT often generate Markdown to format their output, which is then seamlessly converted into rich text by assistant apps. The increased importance of raw text and Markdown in recent years can be attributed to the growth of GenAI.
“For years, organizations have accumulated numerous documents in PDF or slide formats, which are inaccessible to LLMs, particularly RAG systems. With Mistral OCR, our customers can now convert rich and complex documents into readable content in all languages,” stated Guillaume Lample, co-founder and chief science officer of Mistral.
“This is a crucial step toward the widespread adoption of AI assistants in companies that need to simplify access to their vast internal documentation,” he added.
Mistral OCR is available through Mistral’s API platform or its cloud partners, including AWS, Azure, and Google Cloud Vertex. For companies handling classified or sensitive data, Mistral offers on-premise deployment options.
According to Mistral, their OCR model outperforms those from Google, Microsoft, and OpenAI, particularly with complex documents featuring mathematical expressions, advanced layouts, or tables, as well as non-English documents.
Given its specialized functionality, Mistral OCR is also considered faster than existing solutions. This is not surprising when compared to multimodal LLMs like GPT-4o, which offer a broader range of features in addition to OCR capabilities.
Mistral utilizes its OCR API internally for its AI assistant, Le Chat. When users upload PDF files, Mistral OCR processes the documents in the background to understand their content before processing the text.
Developers and companies are likely to use Mistral OCR in conjunction with a RAG (Retrieval-Augmented Generation) system, enabling the use of multimodal documents as input for LLMs. This technology has numerous potential applications, such as helping law firms quickly process large volumes of documents.
RAG is a technique used to retrieve data and utilize it as context for generative AI models, further expanding the capabilities of AI assistants and LLMs.
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