The Interdisciplinary Centre for Security, Reliability and Trust (SnT) at the University of Luxembourg, the Post-trade services provider Clearstream and escent officially started a collaborative partnership for a duration of four years. This joint project aims at researching the potential of Natural Language Processing (NLP) and Artificial Intelligence (AI) in process automation.
At escent, we have always firmly believed accurate requirements analysis can drastically lower errors, and costs derived from them, in any IT project. This initiative meets our statement as it aims at automating complex analysis phases thanks to AI and NLP. This will ultimately result in projects that will be more efficient time- and budget wise.
Prof. Lionel Briand, Vice Director of SnT remembers the importance of precise and consistent requirements: “Nearly 50% of budget overruns in IT projects are caused by inadequate requirements which ripple through system design and deployment. Together with our partners, we will work at the cutting edge of new technology to introduce automation to the requirements engineering process – reducing incompleteness, inconsistency, and ambiguity to a minimum – and facilitating the analysis of system compliance.”(…)
Benoit Cardinael, escent Co-Founder, added: “escent constantly monitors emerging trends in the field of requirements engineering. Defining efficiently high-quality requirements is key to the success of complex IT projects. This research partnership provides us with the unique opportunity to leverage our field expertise of current requirements engineering practices to steer research towards the highest adding value areas. We are thrilled to be associated to this initiative!”*
We look forward to the first results of this research that represents another opportunity for escent to remain at the cutting-edge of requirements analysis.
* source: http://deutsche-boerse.com/dbg-en/media-relations/press-releases/New-partnership-of-industry-and-academia-explores-potential-of-Artificial-Intelligence-and-Natural-Language-Processing/3307106.