Skip to main content

A high performance solution for predictive analytics

Objective

The predictive analytics market is undergoing an impressive growth. Indeed, organizations that incorporate that technique into their daily operations not only better manage the present, but also increase the probability of future success.

Intelnics develops the professional predictive analytics solution called Neural Designer. It makes intelligent use of data by discovering complex relationships, recognizing unknown patterns, predicting actual trends or finding associations. Neural Designer out-stands in terms of functionality, usability and performance.

Current technology lacks from advanced model selection techniques, and usually requires many computational resources. The main challenge for Neural Designer is to include a framework capable of untangling complex interactions in big data sets. In order to do that, the software must achieve ultra high performance by means of more efficient algorithms, code optimization and multi-core processing.

The intended users of the solution are professional data scientists, which work at analytics departments of innovative companies, consulting firms specialized in analytics or research centres. Neural Designer will be capable of analysing bigger data sets in less time, providing our customers with results in a way previously unachievable.

The goal is to successfully market Neural Designer. The feasibility assessment of Phase 1 will help us to validate our working hypothesis regarding technical, commercial, financial and legal issues. This study will allow Intelnics to apply for Phase 2 support, in which Neural Designer will be developed to a level of global competitiveness.

The predictive analytics market is largely dominated by the United States, but completion of this project will introduce a European product in the market place of data science.

Field of science

  • /engineering and technology/electrical engineering, electronic engineering, information engineering/electronic engineering/computer hardware
  • /natural sciences/computer and information sciences/data science/big data
  • /natural sciences/computer and information sciences/data science/data mining
  • /natural sciences/computer and information sciences/artificial intelligence/machine learning/deep learning
  • /social sciences/economics and business/business and management/commerce

Call for proposal

H2020-SMEINST-1-2014
See other projects for this call

Funding Scheme

SME-1 - SME instrument phase 1

Coordinator

ARTIFICIAL INTELLIGENCE TECHNIQUES SL
Address
Calle Del Adaja 10, Parque Cientifico De La Univer De Salamanca
37185 Villamayor - Salamanca
Spain
Activity type
Private for-profit entities (excluding Higher or Secondary Education Establishments)
EU contribution
€ 50 000