AUSTIN, Texas--(BUSINESS WIRE)--Apr 15, 2025--
To solve the increasing pressure developers have to extract reliable and consistent data from business documents, ABBYY today introduced ABBYY Document AI™, available through a self-service application programming interface (API). The ABBYY Document AI API was built with the developer’s experience in mind, allowing users to effortlessly transform unstructured business documents into structured, highly accurate data with just a few lines of code, making it easier to try, integrate, learn and purchase industry leading optical character recognition (OCR) and intelligent document processing (IDP) solutions.
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“As a vanguard of OCR, ABBYY has long had a vibrant community of cutting-edge developers creating transformational solutions with our advanced document AI,” said Nick Hyatt, Vice President, Engineering R&D at ABBYY. “We are providing them a new API with minimal setup, access to ample community resources, and pre-trained models for building proofs-of-concept. ABBYY Document AI API is a major step forward for developing automated document workflows.”
According to IDC 1, the IDP market is projected to grow from $2.4 billion in 2023 to $10.5 billion in 2028 – a 34.9% CAGR driven by increasing cloud adoption, AI maturation and expanded document AI use cases.
Commented Amy Machado, Senior Research Manager, Enterprise Content and Knowledge Management Strategies at IDC, “In the age of AI, OCR is experiencing a true renaissance. Developers struggle with extracting reliable data from documents and will often begin with general large language models for this process. However, they quickly face challenges with hallucinations, data inconsistencies, and errors in document processing, and often lack support for multiple languages, handwriting recognition and complex document structures. There is a need for purpose-built solutions specifically designed for document processing that prioritizes easy integration, flexibility, scalability, accuracy, and consistency.”
The ABBYY Document AI API, initially offered in a technical preview, empowers developers to enhance workflows with pre-trained models to extract data from documents and accelerate automation for complex business processes like KYC, account openings, customs clearance, invoice processing, expense management and order processing. It provides precision OCR that flawlessly preserves a document’s logical structure to provide AI-ready data that is essential to unlocking deep insights in genAI and retrieval augmented generation (RAG) or forming the robust foundation needed to train powerful language models.
For more information about how ABBYY Document AI API enables quick, accurate and effortless data extraction to quickly convert business documents of any type, format or language, comprehensive SDKs for Python, C#, JavaScript and Java, and how to join ABBYY’s Discord community, join the preview list for early access at https://digital.abbyy.com/code-extract-automate-your-new-must-have-ocr-api-coming-soon/?itm_source=pressrelease.
1 IDC: Worldwide Intelligent Document Processing Software Forecast, 2024–2028 (IDC #US52445224, August 2024)
About ABBYY
ABBYY puts your information to work with purpose-built AI. We combine innovation and experience to transform data from business-critical documents into intelligent actionable outcomes in over 200 languages in real time. We are trusted by more than 10,000 companies globally, including many of the Fortune 500, to drive significant impact where it matters most: accelerate the customer experience, operational excellence, and competitive advantage. ABBYY is a global company with headquarters in Austin, Texas and offices in 13 countries, and is the Official Intelligent Automation Partner of Arsenal Women Football Club. For more information, visit www.abbyy.com/company and follow us on LinkedIn, X, Facebook, and Instagram.
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The ABBYY Document AI API provides precision OCR that flawlessly preserves a document’s logical structure to provide AI-ready data that is essential to unlocking deep insights in genAI and retrieval augmented generation (RAG) or forming the robust foundation needed to train powerful language models.
