Why Use Ulysses

Latize Ulysses is an augmented intelligence platform that harmonises disparate internal and external data sets into an intelligent web of data about things – people, products, companies, events, etc. Ulysses helps customers to realise Big Data’s huge potential by relieving data specialists of the need to regularly extract, cleanse & transform data to make it palatable to applications, statistical packages and visualization tools.

Intelligent Data Fusion

Eliminate all information silos and start linking data to get a complete picture.

Link and transform data from different sources in a native language that can be comprehended by computers, leaving no dark data undiscovered.

Any incremental data and attributes will be automatically mapped, linked and instantiated, ensuring users always have a consistent unified view and knowledge of their data at all times

End-user Driven Data Discovery

Self-discovery Data browsing to bring out answers to questions never been asked.

Integrated 360 View on Linked Data discovering natural data segments and identify native relationship and links between data attributes

Faster and Effective Decision Making

Data is held in memory during visualization, rather than having to wait while data is moved from and to disk. It takes advantage of multithreading to work faster in multiprocessor machines. *

Users will require lesser dependency on IT for ad-hoc data requests and spend more time analyzing data rather than data preparation.

Secure and Safe

Data is held in memory during visualization, rather than having to wait while data is moved from and to disk. It takes advantage of multithreading to work faster in multiprocessor machines.*

Users will require lesser dependency on IT for ad-hoc data requests and spend more time analyzing data rather than data preparation.

Reduced Total Cost of Ownership

Self-discovery Data browsing to bring out answers to questions never been asked.

Integrated 360 View on Linked Data discovering natural data segments and identify native relationship and links between data attributes

Enterprise-Class Tried and Tested

Data is held in memory during visualization, rather than having to wait while data is moved from and to disk. It takes advantage of multithreading to work faster in multiprocessor machines.

Users will require lesser dependency on IT for ad-hoc data requests and spend more time analyzing data rather than data preparation.