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UiPath Named a Leader in IDC MarketScape: Worldwide Unstructured Intelligent Document Processing Software 2024 Vendor Assessment

UiPath (NYSE: PATH), a leading enterprise automation and AI software company, recently announced it has been named a Leader in the IDC MarketScape: Worldwide Unstructured Intelligent Document Processing Software 2024 Vendor Assessment*. The inaugural report examines AI technologies within the UiPath Business Automation Platform such as Document Understanding, Communications Mining, Intelligent Document Processing (IDP) optical character recognition (OCR), computer vision, natural language processing (NLP), and machine/deep learning to classify and extract information from structured, semi-structured, and unstructured documents.

According to the report, “UiPath views GenAI and LLMs as a critical technology tool and it is increasingly integrating them throughout all phases of its IDP, communications mining, and automation portfolios. It provides a range of GenAI tooling, provider, and model choices to enable customers and partners to build or leverage out-of-the-box GenAI models for a given use case and/or process flows. Further, UiPath continues to prioritize and deploy enterprise-grade security, privacy, access, context grounding, and control features to ensure that GenAI models and services can be safely and securely utilized in support of mission-critical use cases.”

The report also states: “UiPath’s multi-modal AI focus provides it with the strategic vantage point to continually drive new methods and approaches to maximize the value of traditional (i.e., predictive AI) and GenAI for unstructured IDP.”  

Unstructured document processing is part of many business processes across enterprises – this capability supports needs such as customer relationship management, compliance, bill of ladling, contractual reviews, email triage, and many more. With GenAI and LLMs integrated within UiPath IDP, it can automate document understanding and communications mining at scale and maximize business outcomes.

Graham Sheldon, Chief Product Officer at UiPath, said, “Generative LLMs that are specialized for certain tasks enable enterprise automation at scale. Specialized LLMs in IDP deliver lower error rates, improved performance, and accelerated time to value effectively transform unstructured and semi-structured documents and communications into valuable digitized data that can be used in automated processes. This significantly increases an organization’s operational efficiency. I believe being named a Leader in the IDC MarketScape for Unstructured IDP validates our commitment to innovating in this category because of our focus on performance, broad capabilities, and compliance.” 

The UiPath Platform brings the benefits of GenAI and Specialized AI through automation to every facet of every enterprise. Specialized AI is trained using an organization’s data and optimized for its specific needs, resulting in more accurate and tailored solutions. GenAI can be leveraged to extract unstructured data and to accelerate time to value for IDP deployments—significantly decreasing the model training time. 

UiPath AI capabilities within IDP include:

Document Understanding: AI-powered document classification and data extraction for a wide range of document types and use cases. As part of the UiPath Business Automation Platform, Document Understanding enables end-to-end automation of document-intensive processes across the organization – in finance, customer support, human resources, procurement, and sales, among other functions.

Communications Mining: applies AI to extract intent, context, and data from messages and connects to automation. It delivers AI-driven insights into business communications to help customers track and continuously improve the services they provide to their own customers and employees. 

AI Trust Layer: enhances enterprise data privacy policies and Responsible AI principles with additional software-defined governance to help customers responsibly scale their automation ambitions with GenAI. Our AI Trust Layer emphasizes trust, transparency, and control as its principles. 

Prebuilt GenAI Activities for faster time to value: new prebuilt GenAI Activities utilize the UiPath AI Trust Layer and are easy to access, develop with, and leverage high quality AI predictions in automation workflows that deliver faster time to value. GenAI Activities provide access to a growing collection of GenAI use cases, such as text completion for emails, categorization, image detection, language translation, and the ability to filter out personally identifiable information (PII) enabling enterprises to do more with GenAI. With GenAI Activities, enterprises can reduce time to build and achieve a competitive edge using GenAI to help customize the customer experience, optimize supply chains, forecast demands, and make informed decisions.

Context Grounding to augment GenAI models with business specific data: businesses need a safe, reliable, low touch way to use their business data with AI models. To address this need, UiPath introduced Context Grounding, a new feature within the UiPath AI Trust Layer, that helps businesses improve the accuracy of GenAI models by providing prompts a foundation of business context through retrieval augmented generation. This system extracts information from company specific datasets, like a knowledge base or internal policies and procedures to create more accurate and insightful responses. Context Grounding will enhance all UiPath Gen AI experiences in UiPath Autopilots, GenAI Activities, and intelligent document processing (IDP) products like Document Understanding.

Clipboard AI™: a desktop tool that uses advanced AI and Document Understanding models to take the waste out of copy/paste and bring the power of AI to everyone.

A complimentary excerpt of the IDC MarketScape: Worldwide Unstructured Intelligent Document Processing Software 2024 Vendor Assessment is available here.

*IDC MarketScape: Worldwide Unstructured Intelligent Document Processing Software 2024 Vendor Assessment (doc #US52121324, May 2024)

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