Turning Documents into Data: Docugami-LlamaIndex Webinar on Using Metadata for Greater Accuracy and Precision

It’s no exaggeration to say that data fuels the modern business. Businesses that can harness and leverage their mission-critical data and information are more strategic, more efficient, and more competitive.

Right now, every business is underperforming, because they cannot readily access a huge part of their mission-critical data and information, because it is locked away in contracts and other long-form documents. Identifying and retrieving the information trapped in documents is time-consuming, expensive, and error prone.

Until now.

Thanks to advances in AI, declarative markup, the cloud, and other technologies, it is now possible to unlock all of the data and information from long-form documents, so that it can drive business.

Over the last four years, the team at Docugami has focused on realizing the future of documents. Docugami is a proprietary business document foundation model. Our families of LLMs are trained on millions of Business Documents, ranging from 2.7B parameter to 20B parameter models, with multi-modal inputs in the vision and text domains. When you upload your business documents, Docugami generates in zero shot a document knowledge graph representation, using the XML Semantic model for every document you uploaded. We turn your documents into data, automatically, and that data can then be used to generate abstracts, spreadsheets, or data feeds that can power sophisticated workflows. Docugami is in the market today with paying customers in a variety of industry segments, including Commercial Insurance, Commercial Real Estate, Technology, a wide range of Professional Services, and more.  

Docugami recently collaborated with LlamaIndex on a webinar to discuss how to improve the accuracy and precision of data generation from long-form documents.

Unlike other approaches that may only look for certain types of information, or consider metadata only at the document level, Docugami creates a detailed contextual semantic knowledge graph of each document in its entirety. Our approach identifies each chunk of information within a document, as well as the hierarchical relationship between each chunk. Importantly, Docugami associates metadata with individual chunks of document content, for greater accuracy and precision in data generation.

For more detail, please see the attached video: LlamaIndex Webinar: Document Metadata and Local Models for Better, Faster Retrieval - YouTube

We are laser-focused on transforming business by turning documents into data. And we are committed to working with the community to advance the science and practice of Generative AI for Business Documents. We welcome your feedback on our work, and we look forward to more collaborations!