Latest news with #DocumentAI
Techday NZ
4 days ago
- Business
- Techday NZ
Ataccama ONE brings document AI to Snowflake for better data
Ataccama has announced the integration of its unified data trust platform, Ataccama ONE, with Document AI on the Snowflake Marketplace, allowing businesses to transform unstructured content into structured data for analytics and artificial intelligence applications. The announcement from Ataccama enables enterprises to extract, structure, govern, and monitor the quality of unstructured data, making a greater proportion of their information usable for analytics, AI, and business operations. With the majority of enterprise information now classed as unstructured data and continuing to grow rapidly, many organisations struggle to manage this resource effectively. Industry research from IDC indicates that unstructured data accounts for most enterprise data and is expanding by more than 55% annually. According to market findings, 95% of businesses face difficulties in managing their unstructured data, with over half citing it as the most challenging type of information to govern. Unstructured data frequently remains siloed and difficult to leverage, creating operational risk and impacting the reliability of AI systems as these systems increasingly rely on such data for powering large language models and retrieval-augmented generation applications. Through the integration of Ataccama ONE and Document AI within the Snowflake environment, enterprises can convert documents such as contracts, invoices, and PDFs into structured records. Natural language prompts—such as, "What is the effective date of the contract?"—are processed by the Arctic-TILT large language model developed by Snowflake, generating structured outputs stored directly in Snowflake tables. Ataccama ONE then connects to the resulting data tables to profile the data, perform quality checks, and manage governance policies on the structured outputs. The system also allows companies to follow the data through analytics, reporting, and AI workflows by capturing lineage at the table level. Additional metadata can be added from the original documents to increase traceability where required. This process aims to reduce manual intervention, build trust in the data, and enable repeatable workflows for business teams. Speaking to the importance of unlocking value from unstructured data, Sam Wong, Senior Director of Data & AI at a global beverage company, said: "Unstructured data is an untapped data source as real business context lives there, but it's also the hardest to govern. Documents, contracts, and communications contain the terms, conditions, and risks that structured systems miss. Without a way to extract, validate, and manage that information at scale, AI lacks the foundation it needs to be reliable. With Ataccama ONE and Document AI inside Snowflake, organizations can turn thousands of documents into trusted, structured data. That will give us improved analytics, enhanced data quality, and a better foundation for powerful and trustworthy AI." This integration offers several capabilities for users. Companies can extract structured data from documents using natural language, specifying prompts such as "What is the payment term?" to convert unstructured information into structured outputs without the need for custom code. The extracted data is immediately available for use in reporting, analytics, and AI activities, as it is saved directly into Snowflake tables, ready for consumption by business intelligence tools and model pipelines without further transformation. Ataccama ONE provides automated profiling and rule-based validation to monitor the quality of unstructured data on a continual basis, assisting teams in detecting inconsistencies and managing risks early. Document AI models can be trained and reused within Snowsight, allowing for standardised extraction across various document types at scale, including contracts, invoices, and policies. All processes, validation, and governance are performed natively in Snowflake, reducing integration complexity and improving security. Jay Limburn, Chief Product Officer at Ataccama, said: "Unstructured data remains a black box for most organizations, even as it becomes critical for AI and business operations. Without a way to structure, govern, and trust that information, enterprises risk missing the full value of their data. Ataccama ONE combines data quality, governance, observability, lineage, and master data management in a single platform and now extends those capabilities to unstructured content. This allows organizations to improve trust and confidence in all their data, structured and unstructured alike, and build a stronger foundation for AI, analytics, and operational decision-making." Kieran Kennedy, Vice President, Data Cloud Products at Snowflake, said: "Ataccama's presence on Snowflake Marketplace reinforces the value of our integrated platform approach that allows our partners to bring their innovative solutions to market within the Snowflake environment. With this solution, joint customers have the power to streamline document extraction, ensure data quality, and accelerate insight delivery, all within a governed and scalable environment."
Yahoo
5 days ago
- Business
- Yahoo
Ataccama ONE available on Snowflake Marketplace, integrates Document AI
Organizations can extract, structure, govern, and monitor the quality of unstructured data at scale to make more of their information usable for trusted analytics, AI, and business innovation BOSTON, June 03, 2025 (GLOBE NEWSWIRE) -- Ataccama, the data trust company, today announced at Snowflake's annual user conference, Snowflake Summit 2025, the availability of its unified data trust platform, Ataccama ONE, on Snowflake Marketplace. The launch includes an integration with Document AI, enabling enterprises to turn unstructured content, such as contracts, invoices, and PDFs, into structured data by running models directly within Snowflake. According to IDC, unstructured data now makes up the majority of enterprise information and is growing by over 55% each year. Yet much of it remains siloed, unmanaged, and difficult to operationalize. 95% of businesses struggle to manage their unstructured data, and more than half report it as the most difficult type of information to govern. Most organizations still do not know what is hidden within their unstructured data. This blind spot creates operational risk and undermines the value of AI. As enterprises increasingly use unstructured data to power large language models and retrieval-augmented generation (RAG) applications, managing the quality of that data has become critical to building trusted and reliable AI. Ataccama ONE and Document AI allow organizations to unlock value from unstructured information. Enterprises can turn documents into structured records by using natural language prompts, such as 'What is the effective date of the contract?', which are processed by Snowflake's Arctic-TILT large language model to create structured outputs written directly into Snowflake tables. Ataccama ONE connects to these tables to profile the data, apply quality checks, and manage governance policies on the structured outputs. It also tracks how the data flows into analytics, reporting, and AI workflows by capturing lineage at the table level. Additional metadata about the original documents can be added to enrich traceability if needed. This reduces manual work, strengthens trust in the data, and enables repeatable, reliable workflows across the business. 'Unstructured data is an untapped data source as real business context lives there, but it's also the hardest to govern,' said Sam Wong, Senior Director of Data & AI of a global beverage company. 'Documents, contracts, and communications contain the terms, conditions, and risks that structured systems miss. Without a way to extract, validate, and manage that information at scale, AI lacks the foundation it needs to be reliable. With Ataccama ONE and Document AI inside Snowflake, organizations can turn thousands of documents into trusted, structured data. That will give us improved analytics, enhanced data quality, and a better foundation for powerful and trustworthy AI.' 'Unstructured data remains a black box for most organizations, even as it becomes critical for AI and business operations,' said Jay Limburn, Chief Product Officer at Ataccama. 'Without a way to structure, govern, and trust that information, enterprises risk missing the full value of their data. Ataccama ONE combines data quality, governance, observability, lineage, and master data management in a single platform and now extends those capabilities to unstructured content. This allows organizations to improve trust and confidence in all their data, structured and unstructured alike, and build a stronger foundation for AI, analytics, and operational decision-making.' The integration allows users to: Extract structured data using natural language. Teams can specify the information they want to pull, such as 'What is the payment term?', and quickly transform unstructured documents into structured outputs without custom coding. Make extracted data immediately usable for reporting, analytics, and AI. Outputs are written directly to Snowflake tables and are ready for use across BI tools, operational dashboards, and AI model pipelines without requiring additional transformation. Continuously monitor the quality of unstructured data. Ataccama ONE applies automated profiling and rule-based validation to ensure extracted fields meet enterprise standards, helping teams detect inconsistencies and manage risk early. Scale and standardize document processing across teams. Document AI models can be trained and reused in Snowsight, enabling consistent extraction across contracts, invoices, policies, and other document types at scale. Eliminate data movement and simplify governance. All processing, validation, and governance workflows run natively within Snowflake, reducing integration complexity, improving security, and accelerating time to value. 'Ataccama's presence on Snowflake Marketplace reinforces the value of our integrated platform approach that allows our partners to bring their innovative solutions to market within the Snowflake environment,' said Kieran Kennedy, VP, Data Cloud Products at Snowflake. 'With this solution, joint customers have the power to streamline document extraction, ensure data quality, and accelerate insight delivery, all within a governed and scalable environment.' Read the blog 'From black box to business asset: Solving the unstructured data challenge with Ataccama and Snowflake Document AI.' About Ataccama Ataccama is the data trust company. Organizations worldwide rely on Ataccama ONE, the unified data trust platform, to ensure data is accurate, accessible, and actionable. By integrating data quality, lineage, observability, governance, and master data management into a single solution, Ataccama enables businesses to unlock value from their data for AI, analytics, and operations. Trusted by hundreds of global enterprises, Ataccama helps organizations drive innovation, reduce costs, and mitigate risk. Recognized as a Leader in the 2025 Gartner Magic Quadrant for Augmented Data Quality and the 2025 Magic Quadrant for Data and Analytics Governance, Ataccama continues to set the standard for trusted data at scale. Learn more at Media contact press@ in retrieving data Sign in to access your portfolio Error in retrieving data Error in retrieving data Error in retrieving data Error in retrieving data
Yahoo
5 days ago
- Business
- Yahoo
Ataccama ONE available on Snowflake Marketplace, integrates Document AI
Organizations can extract, structure, govern, and monitor the quality of unstructured data at scale to make more of their information usable for trusted analytics, AI, and business innovation BOSTON, June 03, 2025 (GLOBE NEWSWIRE) -- Ataccama, the data trust company, today announced at Snowflake's annual user conference, Snowflake Summit 2025, the availability of its unified data trust platform, Ataccama ONE, on Snowflake Marketplace. The launch includes an integration with Document AI, enabling enterprises to turn unstructured content, such as contracts, invoices, and PDFs, into structured data by running models directly within Snowflake. According to IDC, unstructured data now makes up the majority of enterprise information and is growing by over 55% each year. Yet much of it remains siloed, unmanaged, and difficult to operationalize. 95% of businesses struggle to manage their unstructured data, and more than half report it as the most difficult type of information to govern. Most organizations still do not know what is hidden within their unstructured data. This blind spot creates operational risk and undermines the value of AI. As enterprises increasingly use unstructured data to power large language models and retrieval-augmented generation (RAG) applications, managing the quality of that data has become critical to building trusted and reliable AI. Ataccama ONE and Document AI allow organizations to unlock value from unstructured information. Enterprises can turn documents into structured records by using natural language prompts, such as 'What is the effective date of the contract?', which are processed by Snowflake's Arctic-TILT large language model to create structured outputs written directly into Snowflake tables. Ataccama ONE connects to these tables to profile the data, apply quality checks, and manage governance policies on the structured outputs. It also tracks how the data flows into analytics, reporting, and AI workflows by capturing lineage at the table level. Additional metadata about the original documents can be added to enrich traceability if needed. This reduces manual work, strengthens trust in the data, and enables repeatable, reliable workflows across the business. 'Unstructured data is an untapped data source as real business context lives there, but it's also the hardest to govern,' said Sam Wong, Senior Director of Data & AI of a global beverage company. 'Documents, contracts, and communications contain the terms, conditions, and risks that structured systems miss. Without a way to extract, validate, and manage that information at scale, AI lacks the foundation it needs to be reliable. With Ataccama ONE and Document AI inside Snowflake, organizations can turn thousands of documents into trusted, structured data. That will give us improved analytics, enhanced data quality, and a better foundation for powerful and trustworthy AI.' 'Unstructured data remains a black box for most organizations, even as it becomes critical for AI and business operations,' said Jay Limburn, Chief Product Officer at Ataccama. 'Without a way to structure, govern, and trust that information, enterprises risk missing the full value of their data. Ataccama ONE combines data quality, governance, observability, lineage, and master data management in a single platform and now extends those capabilities to unstructured content. This allows organizations to improve trust and confidence in all their data, structured and unstructured alike, and build a stronger foundation for AI, analytics, and operational decision-making.' The integration allows users to: Extract structured data using natural language. Teams can specify the information they want to pull, such as 'What is the payment term?', and quickly transform unstructured documents into structured outputs without custom coding. Make extracted data immediately usable for reporting, analytics, and AI. Outputs are written directly to Snowflake tables and are ready for use across BI tools, operational dashboards, and AI model pipelines without requiring additional transformation. Continuously monitor the quality of unstructured data. Ataccama ONE applies automated profiling and rule-based validation to ensure extracted fields meet enterprise standards, helping teams detect inconsistencies and manage risk early. Scale and standardize document processing across teams. Document AI models can be trained and reused in Snowsight, enabling consistent extraction across contracts, invoices, policies, and other document types at scale. Eliminate data movement and simplify governance. All processing, validation, and governance workflows run natively within Snowflake, reducing integration complexity, improving security, and accelerating time to value. 'Ataccama's presence on Snowflake Marketplace reinforces the value of our integrated platform approach that allows our partners to bring their innovative solutions to market within the Snowflake environment,' said Kieran Kennedy, VP, Data Cloud Products at Snowflake. 'With this solution, joint customers have the power to streamline document extraction, ensure data quality, and accelerate insight delivery, all within a governed and scalable environment.' Read the blog 'From black box to business asset: Solving the unstructured data challenge with Ataccama and Snowflake Document AI.' About Ataccama Ataccama is the data trust company. Organizations worldwide rely on Ataccama ONE, the unified data trust platform, to ensure data is accurate, accessible, and actionable. By integrating data quality, lineage, observability, governance, and master data management into a single solution, Ataccama enables businesses to unlock value from their data for AI, analytics, and operations. Trusted by hundreds of global enterprises, Ataccama helps organizations drive innovation, reduce costs, and mitigate risk. Recognized as a Leader in the 2025 Gartner Magic Quadrant for Augmented Data Quality and the 2025 Magic Quadrant for Data and Analytics Governance, Ataccama continues to set the standard for trusted data at scale. Learn more at Media contact press@ while retrieving data Sign in to access your portfolio Error while retrieving data Error while retrieving data Error while retrieving data Error while retrieving data
Forbes
17-04-2025
- Business
- Forbes
Abbyy Joins The Dots With Optical Character Recognition For Developers
Data is for databases. It's clear that information in all its forms generally resides in some form of data store, data repository or data coalition, collection and coalescence tool so that we can go and get it when we need it. This core truth means that data is for databases and databases are for database administrators. But data is also for developers. Software application development engineers take a primary role in wrangling with data management in many scenarios, not least of which is the act of extracting reliable and consistent data from business documents. Because the world of enterprise business has moved (and is still moving) to a digital-first base of operations (you may have heard about so-called digital transformation, just maybe), organizations need to ingest and encode valuable documents (some digital, but still a lot of paper) so that the content they contain can form a functional part of business workflows. But business workflows can get lumpy and suffer from disruptions. What we want are intelligent automation workflows that happen inside business operations with digital documentation from the start. This is the pain point that intelligent automation company Abbyy seeks to address directly with the launch of its ABBYY Document AI service. Stylizing its brand in capitals as it does, Abbyy's new intelligent document processing tool is accessible through what here is defined as a 'self-service' (meaning developers don't need the operations team to enable it) application programming interface. The company says that its Document AI API was built with the developer's experience in mind. It allows software engineers to transform unstructured business documents into structured, accurate data with just a few lines of code. This functionality makes it easier to integrate and work with optical character recognition and intelligent document processing solutions. '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 with a new API with minimal setup as well as access to ample community resources, pre-trained models for building proof-of-concepts and a predictable pay-as-you-go pricing model. Abbyy Document AI API is a major step forward for developing automated document workflows.' According to analyst house IDC, the intelligent document processing market is projected to grow from $2.4 billion in 2023 to $10.5 billion in 2028, This 34.9% CAGR is thought to be driven by a number of factors, with key drivers including increasing cloud adoption and cloud-native development, the maturation of AI services as we move out of the intelligence hypecycle into practical use cases and expanded document AI use cases in general. 'In the age of AI, optical character recognition is experiencing a true renaissance,' said Amy Machado, senior research manager for enterprise content and knowledge management strategies at IDC. '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. [They also] often lack support for multiple [human] 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.' Abbyy says that the Abbyy Document AI API enables software developers to enhance workflows with 'pre-trained models to extract data' from documents, which in turn naturally empowers teams to be able to accelerate automation for complex business processes like KYC (a set of guidelines and principles used mainly by financial institutions to verify and validate new clients, standing for know your customer as it does), business account openings of all forms, customs clearance, invoice processing, expense management and order processing. Abbyy Document AI API enables quick, accurate and effortless data extraction to quickly convert business documents of any type, format or language. According to Abbyy, this new software offering provides 'precision OCR', capable of flawlessly preserving a document's logical structure to provide AI-ready data that is essential to unlocking insights in generative AI and retrieval augmented generation. It can also help with core tasks associated with forming the robust foundation needed to train language models. This news comes on the heels of the company establishing new AI labs across the United States, Hungary and India to accelerate the development of purpose-built AI for intelligent document processing and process automation. 'Our proprietary datasets, AI platform and model research and development combined with our deep domain knowledge create foundational intellectual property that will significantly enhance our core solutions and enable expansion into adjacent enterprise applications. We're building upon decades of leadership in OCR, machine learning, computer vision, and natural language processing while extending innovations in AI with our industry expertise. This integrated approach powers next-generation multimodal models to deliver more robust, consistent outcomes that transform business processes,' said Sanjay Nichani, vice president for, AI & computer vision at Abbyy. We hear a lot from enterprise technology vendors who tell us about their focus on customer experiences and now, more recently, the need to make great customer experiences happen by first enabling good software developer experiences. Underling this truth, Abbyy VP Hyatt has said that, 'The developer experience is a crucial aspect of our product strategy. Our teams look forward to making next-generation ABBYY AI easier to consume with modern APIs and developer tools.' With so much at stake in the data management arena, we clearly need to think about data for databases and database administrators, data for developers as showcased here… and the resultant new data services that consumers will be able to use when AI and automation enters its Industry 3.0 phase which it must next logically do.
