NLG.L Regulatory News (NLG)

13 January 2014

Arria NLG Plc

 ("Arria", the "Company" or the "Group")

Launch of NLG Engine 3.0

Arria NLG plc (AIM: NLG), a leader in the development and deployment of Natural Language Generation ("NLG") technologies, announces the release of the Arria NLG Engine 3.0. This latest version of Arria's NLG engine has the ability to integrate graphical information derived from big data sources with the existing NLG reporting capabilities to provide even more effective decision-support.

Feedback from Arria's clients highlighted the considerable value of embedding NLG generated alerts into a graphical interface environment in real time. As a result of this tight integration, reports produced by the new Arria NLG 3.0 engine support faster, more effective decision-making in high intensity operational environments.

Scientific research on intensive care units conducted by the founding scientists of Arria at the University of Aberdeen (between 2006 and 2010) concluded that medical staff made better decisions when presented with reports that include a combination of text and graphics.

The findings of that research have resulted in these capabilities being translated for use in the Oil and Gas industry. When an equipment alert signals the existence of a problem, the combination of text and annotated graphics makes it easier and quicker for an engineer to understand what the condition of that equipment is and to make the right decision at the right time.

Arria currently has several patents pending in relation to the Arria NLG Engine 3.0. 

Professor Ehud Reiter, Chief Scientist of Arria commented:

"Our research shows that in a decision-support context, some types of information are best presented via graphics and some types via text, with the effectiveness of each modality being dependent upon context such as the expertise of the user and the fault in question.

"The new capabilities of the Arria NLG Engine allow Arria systems to present information in a combination of text and graphics, using the optimal modality. The configurability allows the intelligent optimisation of modalities to be externally specified by domain experts. This more effective information presentation leads to better and quicker decision making."

For further information, please visit www.arria.com or contact: