Ontrack Engenium empowers knowledge workers with the ability to make better,
faster and more informed decisions. Critical knowledge applications can be enhanced
by a full range of search capabilities, from keyword to conceptual, while also
providing non query based automation information organization and navigation
capabilities.
Ontrack Engenium is an award winning and market leader in Conceptual Information
Access Technology. Combining the power of our conceptual search engine with
our automatic clustering engine, Ontrack Engenium connects people with people,
information with related information, and people with relevant information,
without the need for human supervision. Documents are retrieved without requiring
the search terms to be present, and information is organized without requiring
a query, increasing efficiencies in a knowledge economy.
Semetric@ - Conceptual Search
Advanced concept-based search engine is designed to be embedded in a variety
of applications to generate better, faster search results. With the Ontrack
Engenium patented conceptual search capabilities, as well as built-in keyword
and parametric search functionality, users can rapidly find information that
would be time-consuming or impossible to find with a keyword or parametric search
alone.
Autometric@ - Automatic Clustering
Offers a fully automated and scalable ability to cluster documents into meaningful
groups and name them with relevant, content-based labels. Cluster labels provide
a clear indication of the contents, allowing simple navigation and discovery
of the entire universe of available documents.
Cometric - Search Results Clustering
Processes search results from any search engine and automatically organizes
similar results into intelligently labeled clusters. Browse a topic tree of
clearly labeled result clusters that brings depth to your results.
CometricSP - Search Results Clustering
The functionality of Cometric in a Microsoft SharePoint environment. Organizes
search results from Microsoft SharePoint into easily navigated groups, removing
the need for users to look through pages of irrelevant results to find the desired
information.