Data Extraction Generative AI IDP 
AWS Machine Learning Blog
MARCH 20, 2025
Gartner predicts that by 2027, 40% of generative AI solutions will be multimodal (text, image, audio and video) by 2027, up from 1% in 2023. The McKinsey 2023 State of AI Report identifies data management as a major obstacle to AI adoption and scaling. billion in 2025 to USD 66.68
AWS Machine Learning Blog
JANUARY 13, 2025
This is where intelligent document processing (IDP), coupled with the power of generative AI , emerges as a game-changing solution. Enhancing the capabilities of IDP is the integration of generative AI, which harnesses large language models (LLMs) and generative techniques to understand and generate human-like text.
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
AWS Machine Learning Blog
JUNE 18, 2024
This represents a major opportunity for businesses to optimize this workflow, save time and money, and improve accuracy by modernizing antiquated manual document handling with intelligent document processing (IDP) on AWS. This post explores how generative AI can make working with business documents and email attachments more straightforward.
ODSC - Open Data Science
OCTOBER 27, 2023
With Intelligent Document Processing (IDP) leveraging artificial intelligence (AI), the task of extracting data from large amounts of documents with differing types and structures becomes efficient and accurate. The following diagram is how we visualize these IDP phases.
AWS Machine Learning Blog
FEBRUARY 21, 2025
Generative AI is revolutionizing enterprise automation, enabling AI systems to understand context, make decisions, and act independently. Generative AI foundation models (FMs), with their ability to understand context and make decisions, are becoming powerful partners in solving sophisticated business problems.
AWS Machine Learning Blog
JUNE 12, 2024
By using the advanced natural language processing (NLP) capabilities of Anthropic Claude 3 Haiku, our intelligent document processing (IDP) solution can extract valuable data directly from images, eliminating the need for complex postprocessing. && zip -r sharplayer.zip.
AWS Machine Learning Blog
NOVEMBER 13, 2024
The market size for multilingual content extraction and the gathering of relevant insights from unstructured documents (such as images, forms, and receipts) for information processing is rapidly increasing. A predefined JSON schema can be provided to the Rhubarb API, which makes sure the LLM generates data in that specific format.
Expert insights. Personalized for you.
105 
Let's personalize your content