Sinus Iridum
Knowledge through information has proven its worth throughout the ages, but is an increasing challenge as data volume and complexity spirals. A problem often compounded by disparate, inflexible legacy systems struggling to cope.
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We need a new approach
- Knowledge: not restricted by volume or complexity, not constrained by rules based analysis, not curtailed by processing inadequacies.
- Delivery: data available to all, as and when it is needed, even in the most dynamic environment.
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A new way of thinking
- The Uncertainty Engine delivers knowledge as a service: making sense of data through human simulation electronics, employing advanced pattern matching that outperforms current technology, fully adaptive to change without the need for pre-determined rules, spots the unusual or interesting... More...
- Visionary hardware systems: IT strategy as a single service; one copy of the data for the whole organisation; a data structure mapped to the business model, not vice versa; infinitely scalable and adaptive hardware; satisfies the needs of the most demanding organisation on a modest budget... More...
Applications
The Uncertainty Engine has been successfully deployed across a wide range of industries. Identifying patterns of activity within large /complex data sets, pointing to fraud, targeting optimal solutions in data decision models, mitigation of risk, disruption minimisation, critical path analysis, disaster recovery, large volume data analysis and screening in areas such as
| FX trader fraud | Investment Bank trading platforms |
| Financial payments /card systems | Data integration |
| New drug discovery | Genome analysis |
| Disruption recovery sequencing | Data restructuring and de-duplication |
| Speciality chemical analysis | Fraud & Risk |
| Screening Internet activity | High volume data analysis |
A White Paper
by D Goldsworth
The Limitations of Computers Computers are excellent at handling large data spaces where the rules are well known, but are unable to handle large data spaces where the rules are either not fully understood or are constantly changing, as is the case in virtually all the more complex business data systems.
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