Europe urgently needs to restore and intensify its engagement with its past. Time Machine will give Europe the technology to strengthen its identity against globalisation, populism and increased social exclusion, by turning its history and cultural heritage into a living resource for co-creating its future. The Large Scale Research Initiative (LSRI) will develop a large-scale digitisation and computing infrastructure mapping millennia of European historical and geographical evolution, transforming kilometres of archives, large collections from museums and libraries, and geohistorical datasets into a distributed digital information system. To succeed, a series of fundamental breakthroughs are targeted in Artificial Intelligence and ICT, making Europe the leader in the extraction and analysis of Big Data of the Past. Time Machine will drive Social Sciences and Humanities toward larger problems, allowing new interpretative models to be built on a superior scale. It will bring a new era of open access to sources, where past and on-going research are open science. This constant flux of knowledge will have a profound effect on education, encouraging reflection on long trends and sharpening critical thinking, and will act as an economic motor for new professions, services and products, impacting key sectors of European economy, including ICT, creative industries and tourism, the development of Smart Cities and land use. The CSA will develop a full LSRI proposal around the Time Machine vision. Detailed roadmaps will be prepared, organised around science and technology, operational principles and infrastructure, exploitation avenues and framework conditions. A dissemination programme aims to further strengthen the rapidly growing ecosystem, currently counting 95 research institutions, most prestigious European cultural heritage associations, large enterprises and innovative SMEs, influential business and civil society associations, and international and national institutional bodies.

Today, enterprises, consultants and clerks manually process data from arbitrary documents (such as insurance policies, contracts, claims, etc.) to enter the necessary process data into their core ERP systems. As a result, it still relies on the physical availability of employees, and is therefore hardly scalable and sensitive to human error. Automation of document processing operations is challenging due to the variety of processes involved, the requirement for high-level recognition technologies, high demands on accuracy, and the versatility of enterprise IT systems. Qidenus Group GmbH was founded in 2015 in Berlin, offering innovative software-based document management services. It has been our mission to support archives and operational processes to unlock information from all types of documents with our SearchInk technology, which combines Machine Learning, Semantic Processing and Layout and Structure Analysis. Now, we want to implement SearchInk into the B2B-market by offering omni:us, a highly scalable, digitalised SaaS-platform for automated data classification, extraction and the hand-over process to core ERP-systems in the business segment of Claim Management as beachhead market. Thanks to the performance of omni:us, the efficiency, speed and quality of data extraction and archiving will be dramatically increased, resulting in reductions of working time to <5% and costs up to 90%. The use of omni:us will offer enterprises a 100+% increase in turnover, 85-95% reduction of labour time spend, and automatically declining error rates (<5%). In this Phase 2 project, we intend to further deploy the omni:us SaaS architecture from a technological perspective with improved SearchInk technology performance, and Claim Managementspecific functionalities in a SaaS environment. Also, to grow our business, we want to create API´s to expand the compatibility with common ERP-systems and develop the market to ensure successful market launch.