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00:00:00 – 00:13:26
In the video, Michael Hill and Kyle Kissle discuss the development and enhancement of Pattern Builder Max, a product from NetDocuments created through the acquisition of AfterPattern, a no-code document automation platform. This acquisition enabled NetDocuments to integrate advanced workflow and document automation capabilities into their existing document management system (DMS), significantly aided by generative AI technologies.
The conversation emphasizes ensuring security and privacy when integrating non-public, client-specific details into AI processes, achieved through a partnership with Microsoft. Enterprise-grade security measures like zero-day retention and zero-read agreements are highlighted, which are crucial for legal professionals managing sensitive information.
The video also explores the pattern Builder tool, which enhances document review processes by combining document knowledge with large language models while maintaining organizational control and flexibility. A practical example involving the review of a non-disclosure agreement (NDA) is demonstrated, showcasing the application of predefined policies and secure processing.
Generative AI workflows are discussed in detail, including their integration within NetDocuments matter files for tasks such as creating funding packets and reviewing documents. The importance of validating AI outputs before using them in client-facing contexts is stressed. This functionality allows users to create summaries and timelines from multiple documents, aiding new attorneys in quickly understanding cases.
The video concludes with an overview of how AI speeds up processing and generating case digests, ensuring confidentiality and security, and maintaining ease of access through low code functionality combined with large language models. Viewers are invited to contact NetDocuments for more information about Pattern Builder.
00:00:00
In this part of the video, Michael Hill and Kyle Kissle discuss the creation and evolution of Pattern Builder Max, a product from NetDocuments. Michael explains that Pattern Builder Max originated with the acquisition of AfterPattern, a no-code document and workflow automation platform. This acquisition allowed NetDocuments to integrate advanced automation capabilities with their existing document management system (DMS). They leveraged generative AI to further enhance the product, meeting the complex needs of their clients, including legal departments and law firms. Michael highlights that Pattern Builder Max has become their most successful release. Kyle adds that careful consideration was given to integrating generative AI responsibly, ensuring that it leverages user knowledge without compromising control and governance. The focus for clients is to have AI tools that embody their expertise and integrate seamlessly with their documents.
00:03:00
In this segment of the video, the discussion focuses on the integration of non-public, client-specific details into AI processes while ensuring security and privacy through a partnership with Microsoft. They highlight the establishment of enterprise-grade security measures such as zero-day retention and zero-read agreements, meaning that neither Microsoft employees nor algorithms have access to users’ data. This is particularly crucial for legal professionals who handle sensitive information. The video also compares traditional chatbots, which require users to become prompt engineers, to more advanced solutions that offer better control over content and input, ensuring compliance with legal guidelines and user needs.
00:06:00
In this segment of the video, the speaker introduces the “pattern Builder” tool, which automates text processing by combining document knowledge with large language models. This approach removes obfuscation from blackbox models while maintaining organizational control and flexibility. The speaker demonstrates a use case involving the review of a non-disclosure agreement (NDA) using generative AI. The process involves selecting the document, applying pre-defined policies, and securely processing it with Microsoft services. The AI assesses the document against criteria, suggests changes with semantic redlining, and ensures the document aligns with policies. Importantly, the system retains data privacy and security within the net documents ecosystem without needing external data migration.
00:09:00
In this part of the video, the speaker explains how generative AI workflows can be integrated directly within NetDocuments matter files. Users can trigger various workflows, such as creating a funding packet or reviewing documents. They discuss both out-of-the-box and custom applications, using the example of generating multiple documents by extracting data from a source document and validating it before storing it in a relational database. The speaker highlights the importance of validating AI outputs before using them in client-facing documents. Additionally, they demonstrate creating a succinct timeline of events from multiple documents to help new attorneys get up to speed quickly. This involves summarizing large volumes of text, performing searches, and saving case digests back to the matter file for easy review and quality assurance.
00:12:00
In this segment of the video, the speaker discusses how AI is used to speed up processing and generating case digests across multiple documents. A disclaimer is included to inform users that AI was used. The generated file contains a summarization of all selected documents, providing a timeline of key events in either chronological, reverse chronological, or original order. This solution addresses issues of confidentiality, security, and ease of access, combining low code functionality with the power of large language models. The segment concludes with an invitation for viewers to contact Net Documents for more information about Pattern Builder.