What is Biz7?
Numerous business activities result in the production of a significant amount of documents, which can create difficulties in finding and managing pertinent information tied to specific files, contexts, or terms. Luma7 effectively tackles these issues by generating automatic links between documents without the need for keywords, metadata, or tagging systems. Utilizing advanced algorithms, it scrutinizes the text within each document to identify potential relationships, thereby exposing the connections that exist among different files. This innovative system simplifies the oversight of generated documents, allows for the linking of various documentation sources, and guarantees the automatic creation of links across a multitude of files. Moreover, it establishes relationships between different concepts and documents, provides automated tagging that incorporates relevant keywords that may not be included in the text, and applies connection processes throughout the entire archive of articles. It also includes entity recognition capabilities that span across multiple documents and offers support for a variety of languages, thereby increasing its adaptability and usefulness for an array of business requirements. Ultimately, Luma7 revolutionizes how organizations handle their documentation by making access to interconnected information more straightforward and efficient, thus fostering better decision-making and collaboration.
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Company Facts
Company Name:
Luma7
Company Location:
Switzerland
Company Website:
luma7.com/biz/biz7.php
Product Details
Deployment
SaaS
Training Options
Documentation Hub
On-Site Training
Support
Web-Based Support
Product Details
Target Company Sizes
Individual
1-10
11-50
51-200
201-500
501-1000
1001-5000
5001-10000
10001+
Target Organization Types
Mid Size Business
Small Business
Enterprise
Freelance
Nonprofit
Government
Startup
Supported Languages
English
Biz7 Categories and Features
Text Mining Software
Boolean Queries
Document Filtering
Graphical Data Presentation
Language Detection
Predictive Modeling
Sentiment Analysis
Summarization
Tagging
Taxonomy Classification
Text Analysis
Topic Clustering