Extract Valuable Insights from Unstructured Data

In many organizations, a large portion of data is stored in the form of free text. Hume is a powerful tool that helps you extract new knowledge from unstructured data and make it available in the knowledge graph. With Hume's out-of-the-box natural language processing (NLP) capabilities, it is easy to plug in existing services and language models, simplifying the process of extracting insights from unstructured data.

Hume NLP features are an invaluable asset for any organization looking to gain a deeper understanding of their data. In the field of criminal intelligence, Hume NLP capabilities can help law enforcement agencies analyze social media data, intercepts, and other types of unstructured data to uncover hidden patterns and relationships, identify potential threats, and inform their decision-making processes.

Benefits of Unstructured Data Processing

  • Documents are not considered isolated: Hume document analysis capabilities take into account the connections and relationships between documents, helping you gain a more comprehensive understanding of your data.

  • Gain multiple, flexible, and unexpected access patterns: Hume flexible access patterns allow you to explore your data from multiple angles, uncovering new insights and patterns that may not have been apparent before.

  • Integrate with other Machine Learning approaches: Hume document analysis capabilities can be easily integrated with other Machine Learning approaches, such as recommendations, to enhance your analysis and uncover deeper insights.

  • Integrate with other tools: Hume document analysis capabilities are easy to integrate with other tools, such as Huggingface, making it simple to incorporate these capabilities into your existing workflow.

  • Create a knowledge graph: Hume document analysis capabilities help you create a knowledge graph, organizing and structuring your data in a way that is easy to understand and navigate.

  • Enable AI: Hume document analysis capabilities enable you to harness the power of AI to extract valuable insights from your data and drive better outcomes.

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Feature Building Blocks

Textual Documents Support

Load and parse documents of different types: plain text, PDF, Word, or Excel. Hume converts the content and metadata into nodes and relationships, creating robust knowledge graphs.

Website parsing

Crawl entire websites - Hume converts the structure, metadata, and content into nodes and relationships and enriches your existing knowledge graph.

Named Entity Recognition

Automatically recognise domain-specific entities that are vital to your organisation and use case.

Named Entity Recognition (BERT)

Leverage latest techniques based on deep learning for identifying named entities using contextual information from the text.

Entity Relationship Extraction (Rule Based)

Avoid training complex machine learning models and specify rules to reveal connections among entities.

Entity Relationship Extraction (ML)

Automatically convert free text sentences into relationships and nodes using machine learning models.

Keywords Extraction and Topic Modelling

Extract relevant keywords and key phrases from free text using Hume's proprietary, unsupervised keyword extraction algorithm.

See what Hume can do for you - Book your live demo

Just fill in the Contact Form and our team of experts is ready to show you a live demo and answer all your questions.

What to expect:

  • A brief introduction to focus on your organisation's unique needs and requirements.
  • A live demo of Hume tailored to your specific project or domain
  • Zero commitment

Ready to try Hume after the demo?

  • Get access to a free, full-featured trial of Hume on your infrastructure all with the support of our engineers
  • Fine tune your experience and launch to production