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Editorial Advisory Board

  • Professor Andrea M. Armani, University of Southern California
  • Ruti Ben-Shlomi, Ph.D., LightSolver
  • James Butler, Ph.D., Hamamatsu
  • Natalie Fardian-Melamed, Ph.D., Columbia University
  • Justin Sigley, Ph.D., AmeriCOM
  • Professor Birgit Stiller, Max Planck Institute for the Science of Light, and Leibniz University of Hannover
  • Professor Stephen Sweeney, University of Glasgow
  • Mohan Wang, Ph.D., University of Oxford
  • Professor Xuchen Wang, Harbin Engineering University
  • Professor Stefan Witte, Delft University of Technology

UiPath Named a Leader in Document Mining and Analytics Platforms by Independent Research Firm

UiPath (NYSE: PATH), a leading enterprise automation and AI software company, today announced it has been named a Leader in The Forrester Wave™: Document Mining and Analytics Platforms, Q2, 2024*.

The report stated, “Platform strengths include HITL accuracy verification and improvement processes, ML-based AI, document labeling (for supervised ML), use of genAI in document mining processes including pre- (prompt engineering, RAG) and post-processing (validation) of data, classifying and categorizing documents, multiple deployment options, workflow orchestration, mining information from complex forms and documents, broad security and regulatory compliance capabilities…. Reference customers praised the platform’s business value, time to value, the overall relationship with the vendor, HITL accuracy verification, business user self-service capabilities, cross document mining, architecture, data security capabilities, and data / analytics UX. One reference customer specifically cited integration of document processing and process automation as a differentiator.”

The report also stated, “UiPath is an excellent choice for clients seeking an integrated solution that combines document mining, analytics, and process automation platform to tackle a wide range of automation use cases.”

UiPath Intelligent Document Processing (IDP) leverages automation, specialized AI, and GenAI to blast through common roadblocks that have historically inhibited modernization of document processing and understanding. These roadblocks include challenges in handling high variability in document formats, difficulty in handling unstructured data, and laborious model training. Recently, UiPath released Large Language Models (LLMs) within UiPath Document Understanding, which improve the platform’s ability to accurately process freeform unstructured documents like legal agreements, contracts, and emails at high scale.

The new LLMs, DocPath and CommPath, provide businesses LLMs that are extensively trained for their specific tasks—document processing and communications. Instead of relying on imprecise and time-consuming prompt engineering, DocPath and CommPath enable enterprises with extensive tools to customize AI models to their exact requirements, allowing them to understand any document and a huge variety of message types.

In testing performed by UiPath, compared to leading GenAI models, DocPath error rates were 45% to 76% lower. Moreover, in interpreting complex table structures, UiPath DocPath outperformed other IDP and GenAI vendors by registering 30-65% fewer extraction errors. GenAI within UiPath IDP also dramatically reduces the effort it takes to train models to understand specific documents and forms—cutting the time up to 80%, from weeks to hours or a day or two.

“Enterprises in every industry still struggle with time-consuming, manual data entry to process information locked within documents. Our LLMs, DocPath and CommPath, are built around specialized knowledge based on our extensive experience in targeted industries and business processes. They are tuned to process complex business documents and diverse communications, from intricate interactions to free-form documents and tables,” said Graham Sheldon, Chief Product Officer at UiPath. “By narrowing the focus, but retaining the vast power of GenAI, our specialized LLMs can significantly outperform the output accuracy of currently available LLMs, which is critical in delivering efficient, trustable IDP.”

To address enterprises’ need for safe, reliable ways to use their business data with AI models, UiPath also introduced Context Grounding, a new feature within the UiPath AI Trust Layer now in private preview. UiPath Context Grounding 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 makes business data ideal for LLMs by converting it to an optimized format that can easily be indexed, searched, and injected into prompts to improve GenAI predictions. Context Grounding will enhance all UiPath Gen AI experiences in UiPath Autopilot™, GenAI Activities, and IDP products like Document Understanding.

To download a complimentary version of The Forrester Wave™: Document Mining and Analytics Platforms, Process Automation, Q2 2024 report, please visit here.

*The Forrester Wave™: Document Mining and Analytics Platforms, Q2 2024, May 30, 2024

About UiPath

UiPath (NYSE: PATH) is on a mission to uplevel knowledge work so more people can work more creatively, collaboratively, and strategically. The AI-powered UiPath Business Automation Platform combines the leading robotic process automation (RPA) solution with a full suite of capabilities to understand, automate, and operate end-to-end processes, offering unprecedented time-to-value. For organizations that need to evolve to survive and thrive through increasingly changing times, UiPath is The Foundation of Innovation™.

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