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Document AI: Accelerated Document Processing for Efficient Data Extraction

Document-intensive workflows and processes have traditionally consumed significant time and resources. Document AI, a type of document intelligence, dramatically accelerates these workflows and processes. Document AI is a fully managed workflow that uses Arctic-TILT for efficient extraction of text, table values and handwritten content from PDFs and other unstructured documents into a structured output. Using this technology, organizations can analyze and organize data contained in invoices, reports, intake forms, and many other electronic and handwritten documents. In this article, we explain how document intelligence works, and we explore several examples of how organizations are using it to extract value from their business documents.

How Does Document Intelligence Work? 

Manually analyzing documents is a time-consuming, error-prone and resource-inefficient process. Document AI, on the other hand, provides intelligent automation, allowing organizations to quickly extract relevant information from unstructured text documents and make it available for use within seconds. Document intelligence solutions can automate a range of manual workflows, including invoice processing, extraction of patient information from medical records, and the streamlining of loan underwriting by identifying and organizing key information from loan applications, and supporting documents — all while eliminating human error. 

Snowflake Snowday 2021

Document intelligence uses artificial intelligence to automatically classify, extract and organize data from unstructured documents. In the case of physical documents, including printed forms or forms filled out by hand, the process starts with optical character recognition technology scanning the documents to convert handwritten text into digital text. Once the documents have been converted into a format readable by machines, they’re automatically sorted into categories.

Documents are then classified using a set of predefined rules customized to the use case, or, in more advanced systems, trained AI models that automatically classify documents into the appropriate categories. Documents that are incomplete or contain missing values or other errors may require human intervention to resolve before they can be included. From there, the data is extracted from the documents and placed into a structured format that makes it available for users to analyze, collaborate on or use for other business processes. 

Document Intelligence in Action

Document AI provides machines with the ability to "read" and comprehend documents in a similar way as humans do. Here are just a few examples of how document intelligence is transforming the ways organizations extract value from their business documents.

Extracting data for compliance

Document AI converts the unstructured data contained in documents into a format that can be easily sorted, organized and analyzed. The AI models powering document intelligence solutions can be trained to extract specific data from text-based sources. Contract analysis is one example. An organization can use document intelligence to review their vendor contracts, quickly extracting the information needed to verify compliance with organizational policies.

Translation documents for multilingual analysis

For organizations that operate across borders, documents are not always written in a single language. With automated language translation, AI-enabled document intelligence solutions can translate unstructured text. A multinational brand could use this feature to analyze online reviews, survey responses and customer service transcripts across the organization’s geographical locations.

Document classification 

Document AI can identify and categorize documents based on content and purpose, helping organizations identify and secure documents that contain sensitive or regulated data. Numerous industries — including healthcare, finance and retail — process, store and analyze large amounts of sensitive data that is subject to data privacy regulations. 

Document AI in Snowflake Cortex AI: Process Any Document and Get Answers Fast

Document AI is part of Snowflake Cortex AI, and provides organizations with the tools to automatically classify, extract and enrich document data at scale. Using a pre-trained LLM and intuitive interface, users can process any document (PDF, Word, text, screenshots) into structured output to get answers to their questions. 

Empowering the domain expert

Document AI clears away many of the technical hurdles that have prevented experts from taking the lead in model management. Eliminating the need for machine learning or SQL expertise, domain experts can deploy their content knowledge to test their models with robust, domain-specific insights. 

Snowflake unlocks the potential bound up in unstructured text documents. Organizations leveraging Cortex AI can streamline document-intensive workflows, boost productivity, and quickly extract and analyze data from large volumes of unstructured documents.

Natively integrating the AI Data Cloud with Powerful LLM models

Besides Document AI, customers can leverage cost-effective LLM-based models to conduct document intelligence activities in seconds by using the following features:

  • Sentiment detection: Detect sentiment of text across your table.

  • Text summarization: Summarize long documents for faster consumption.

  • Translation: Translate text at scale. 

Snowflake Cortex AI allows domain experts and other data users to extract information from their documents by simply asking questions in the same way you’d ask questions of another human.