Sclable launches new­­ AI-Unit.

Sclable expands its service portfolio to include AI-as-a-Service and data science consulting.

from Nina Vutk, on 27.06.2019

Small and large companies across Europe have an increasing need for expertise in the field of applied artificial intelligence. By 2035, the use of AI is expected to increase the productivity of companies across Europe by up to 38 percent, as artificial intelligence has the potential to help companies of all sizes across all industries work more efficiently and intelligently. And if Europe on average develops and implements AI based on its current assets and digital position relative to the world, it could contribute around 2.7 trillion euros or 20 percent to its total economic output by 2030.

In Austria, only 42 percent of domestic companies are currently actively involved in the use of artificial intelligence. According to a recent study by Accenture Austria, Austrian economic growth could be more than doubled from 1.4 percent per year to three percent through the use of AI. This would result in an additional gross value added of 122 billion euros in 2035.

Sclable and its AI team are starting right here and are expanding their service- and product portfolio to include AI-as-a-Service, which is intended to support Austrian and European traditional industrial companies in independently developing and implementing AI projects. For this purpose, Sclable provides - among other products and services - the "Sclable AI Toolbox", which enables solid programmers to provide complex AI software within a few weeks.

Note: Sclable's AI Hub will be officially launched in Q4 2019.

What Sclable’s AI Hub is offering:

  • Clearly defined strategy consulting services by technical domain experts to identify use-cases for AI and Data Science. 
  • A high-performance AI library that allows developer teams to quickly and effectively implement AI products within their organization.
  • Research and supervision from senior researchers that provides existing in-house data science teams to take on complex and challenging projects.
  • Management consulting for AI project owners and managers from experienced senior consultants to drive the necessary culture and project practices.

The Sclable Senior Research Team – Leads.

Sanchit Singh, MSc, Lead Computer Vision - Dr. Viktor Sandner, Lead Data Science - Frank Fichtenmüller, Chief Data Officer - Dr. Charles Dietz, Lead Machine Learning
  • Frank Fichtenmüller, Chief Data Officer: Frank took the lead on data strategy at Sclable in October 2018 while still owning the technical lead for the product development and consulting services in the AI team. After four years spent growing two international AI startups in Vienna and Shanghai, he brought his extensive global network and full-stack AI competences to drive the setup and expansion of a world-class applied research team here in Vienna.
  • Dr. Charles Dietz, Lead Machine Learning: Charles drives simulation and numerical computation methods for model-based machine learning. He works from a background in particle physics and a substantial work experience in CERN as well as product start-ups around data-driven methodologies.
  • Dr. Viktor Sandner, Lead Data Science: Viktor leads the section on data science and methodology, driving projects from the initial data analysis, through the definition of targets to the evaluation of existing data sources. His work in modeling complex production processes in the field of bioprocess engineering at Fujifilm Diosynth Biotechnologies allows him to quickly maneuver complex data integration processes.
  • Dr. Gábor Recski, Lead NLP research: Gábor recently took up the lead for natural language processing, navigating complex analysis of text documents, from large document collections to real-time streaming data for our clients. As a former assistant professor at the TU Budapest and scientific lead of the successful NLP Startup, he has been leading research in the field since 2006.
  • Sanchit Singh, MSc, Lead Computer Vision: Sanchit joined to lead the teams’ work on computer vision, enabling modern automatic image recognition and classification tasks for automated decision making. His strong experience in product development around computer vision products in healthcare with his former projects have showcased many aspects of applied AI.