Introducing

Bringing Visibility and Explainability to GenAI-Assisted Analysis Across Large Collections of Documents
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Over 80% of enterprise data lives in unstructured forms, PDFs, emails, reports, regulatory filings. Most of the time, such sources contain critical business information, yet they remain difficult to access and reason over at scale
GraphXR, developed by Kineviz, is a generative AI tool designed to enhance the analysis of extensive text-based information. It automatically extracts entities and their relationships from documents, creating visual knowledge maps that facilitate rapid navigation and document review. This approach enables users to efficiently summarise, contextualise and analyse large volumes of unstructured data, uncovering evidence, themes, relationships and key topics. By integrating locally hosted large language models or OpenAI with robust graph databases like Neo4j, GraphXR provides a flexible and secure platform for comprehensive data visualisation and analysis.
AI Bulk-Data Analysis
Discover, explore and map extensive caches of electronically stored information, including documents, emails, attachments and messages. Effortlessly summarise, contextualise and analyse large volumes of information. Uncover critical evidence, themes, relationships, connections, key topics, time-sensitive events and their consequences using the power of artificial intelligence.



Contact

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Graph XR tools provide an end-to-end solution that turns graph-based reasoning, evidence-first analytics, and interactive exploration into a single, streamlined pipeline that unlocks the intelligence trapped within unstructured data


