Mistral releases new OCR API, claiming the best performance in the world

Well funded French AI startup Mistral prefers to do things its way.

The company has developed a new reasoning model in a sea of competing models. Mistral OCR is a new optical character identification (OCR), API that provides advanced document understanding capabilities.

This API extracts content, including handwritten notes and typed text from unstructured images and PDFs with high accuracy. It then presents it in a structured format.

A structured data is a set of information that has been organized in a specific way, usually using rows and column, to make it easier to search and analyze. Examples include names, addresses, and financial transactions stored on spreadsheets or databases.

Unstructured data, on the other hand, lacks a particular format or structure and is therefore more difficult to process and analyse. This category includes a wide variety of data types such as emails and social media posts. It also includes videos, images, audio files, and images. Since unstructured data does not fit neatly in traditional databases, specialized techniques and tools, such as natural language processing (NLP), and machine learning (ML), can be used to extract meaningful insights. Understanding the differences between these data types are crucial for businesses who want to manage and leverage their assets. Mistral OCR’s multilingual support, rapid processing speeds, and integration with large-language models (LLMs), for document understanding, are all designed to help organizations make their documentation AI ready.

According to Mistral’s announcement of the new API, 90% of all business data is unstructured. The new API will be a great help to organizations that want to digitize their data and catalog it for use in AI applications.

Mistral is the new gold standard in OCR.

Mistral OCR improves how organizations analyze and process complex documents.

Mistral OCR, unlike traditional OCR solutions, which focus primarily on text extraction, is designed to interpret different document typographical elements, such as tables, mathematical expressions, and interleaved pictures, while maintaining structured outputs. According to Mistral’s chief scientist Guillaume Lample this technology represents an important step towards AI adoption by enterprises, especially for companies that want to simplify access to internal documentation.

Le Chat, the document processing tool used by millions of users, already integrates the API. Developers and businesses can now access the model through Mistral’s developer suite, La Plateforme.

The API will also be available through cloud and inference partner and will offer on premises deployment for organizations that have high security requirements.

Advancement of a 70-year-old computing technology

OCR has played an important role in automating document digitization and data extraction for decades. In the 1950s, David Shepard, his colleagues Harvey Lawless Jr. and William Lawless Sr. developed the first commercial OCR machines. They founded Intelligent Machines Research Co. to bring this technology to market.

The system was popularized when Reader’s Digest, followed by major oil companies, banks, and telecom companies such as AT&T, became its first large customer. IBM introduced its OCR machine in 1959 after licensing IMR’s patents. This was the first time that the term became the industry standard.

OCR technology has evolved since then, incorporating AI, ML, and other technologies to improve accuracy and expand language support. It is now found in enterprise software such as PDF reader. Adobe Acrobat (version 19459079).

Mistral is the next evolution in document comprehension, as it uses AI to enhance document understanding beyond simple text recognition.

Benchmarks demonstrate the power of Mistral OCR.

Mistral highlights OCR’s competitive advantage over existing tools by citing benchmark tests in which it outperformed major competitors including Google Document AI and Azure OCR, as well as OpenAI’s GPT-4o.

This model achieved the highest accuracy in math recognition, multilingual text processing and scanned documents.

Mistral OCR is also designed to operate faster than competing models and is capable of processing up to 2,000 pages per minute on a single node.

This speed advantage makes it suitable for high-volume document processing in industries such as research, customer service and historical preservation.

Sophia Yang, head of developer relations at Mistral, has been On her X account, she actively showcasedOCR capabilities. She highlighted its top-tier benchmarks for performance, multilingual support, and ability to accurately extract math equations from PDFs.

The following is a transcript of a conversation between a woman and Jeremy. In a recent postshe shared a successful example of Mistral’s OCR recognizing and formatting complex mathematic expressions. This further demonstrates its effectiveness in scientific and academic applications.

Key features and use-cases

Mistral OCR offers several features that make it an effective tool for businesses and organizations handling large document repositories.

• Multilingual processing and multimodal processing This model supports a variety of languages, scripts, and document layouts. Yang called this capability a game changer for multilingual document handling. Structured outputs and document hierarchy preservation
• Mistral OCR preserves formatting elements like headers, paragraphs and tables. This ensures that extracted text is useful for downstream applications.Document-as prompt and structured outputs: Users can extract content and format it into structured outputs such as JSON and Markdown. This allows integration with other AI driven workflows. Self-hosting: Organizations with strict data security and compliance needs can deploy Mistral OCR in their own infrastructure.

Mistral AI developer Document understanding capabilities go beyond OCR in the documentation online . Mistral OCR integrates LLMs after extracting text and structure. This allows users to interact with the document content using natural-language queries. This feature allows:

• Question-answering about specific document content,
• Automated data extraction and summarization,
• Comparison across multiple documents,
• Contextual responses that consider the entire document.

What enterprise decision-makers should know about Mistral OCR.

CEOs, CIOs and CTOs, IT Managers and Team Leaders can benefit from Mistral OCR’s efficiency, security, and scalability when it comes to document-driven workflows.

1. Mistral OCR increases efficiency and reduces costs

by automating document processing, reducing manual data input and streamlining operations. The ability to process large volumes of document faster and more accurately, while reducing the need for manual intervention, allows organizations to reduce their administrative overhead. This is especially useful for industries such as finance, healthcare and legal, where paperwork is a major bottleneck.

2. AI-driven insights for enhanced decision-making

Mistral OCR’s document understanding capabilities enable decision-makers extract actionable insights out of reports, contracts and financial documents. IT leaders can integrate this API into their business intelligence platforms to enable AI-assisted documents analysis, which supports faster and data-driven decisions.

3. Data security and compliance improved

Mistral OCR’s on-premises deployment meets the compliance and security needs of enterprises that handle sensitive or classified information. CIOs and compliance officials can ensure that proprietary data remains within the internal infrastructure, while leveraging AI to process documents.

4. Integration with enterprise workflows is seamless

CTOs, IT managers, and legal tech experts can integrate Mistral OCR into existing enterprise systems such as content management platforms, CRM solutions, AI-driven assistants, and legal tech solutions. The API’s support of structured outputs (JSON and Markdown) makes automating document-based workflows easy, improving productivity.

5. AI-driven innovation can give you a competitive advantage

If your organization is looking to stay on top of digital transformation, Mistral OCR provides a scalable AI solution that makes large document repositories easier to access. By leveraging AI to extract information, enterprises can improve customer experiences, optimize their internal knowledge bases, and reduce operational inefficiencies.

Pricing and availability

Mistral’s OCR is priced at $1 per 1,000 pages, while batch inference is priced at $1 per 2,000 pages.

Mistral plans to expand the API to cloud and inference partners soon. The model can also be downloaded for free from Mistral’s site. The catis a conversational bot powered by its LLMs, similar to and competing with OpenAI’s ChatGPT. It allows users to test out its capabilities before integrating them into their workflows. Mistral AI will continue to improve the model in the coming weeks based on feedback from users.

I tested it briefly on a handwritten (and messy!) note on a scrap piece of paper. It returned an accurate, structured line of text in less than a second.

What’s next? Mistral OCR is the latest addition to Mistral AI’s suite of AI-driven products, aimed at enterprises who require high-performance solutions for document processing. Mistral’s AI-powered document understanding combines OCR with AI to enable businesses to extract, analyse and interact with documents in a more intelligent way.

Enterprises, developers, and IT teams can explore the Mistral OCR platform or request an on-premises deployment to meet specific use cases.

Alternatively, developers can check out Mistral AI documentation is required to start using mistral-ocr.