The main goal of the project is to make available the knowledge contained into digital images of handwritten documents in
the same way it is currently possible to do for native digital documents, and independently of the language, the alphabet and
the writer of the documents.
It is addressed to any public or private organization dealing with handwritten documents, whatever is the area of application
(e.g. historical, cultural, economic, financial, administrative, legal, medical and so on).
The expected impact of the project is creating an absolutely new segment in the ICT Solutions market, with an economic
volume of at least hundreds of million euros. The impact for the Applicant is estimated at least in 40M€ turnover after three
years, with a proportional growth of annual profits. The number of employees after 3 years is expected to be over 200
The Phase 1 of the project will last about five months, starting on June 2017.
The objective of Phase 1 is to draw up a feasibility study and a business plan, aimed at verifying and quantitatively specify in
details all the relevant aspects of the project, through the following activities:
- A technological assessment, aimed at evaluating the feasibility of the concept, the development of innovation strategy and
- A marketing assessment, aimed at confirming the target market segments at international level and defining the short/
medium term marketing plan;
- An Operating Assessment, aimed at evaluating risks, economic financial and other organisational aspects.
The Applicant is an early stage high risk innovative SME in the ICT sector owning a new patented technology, based on
innovative ICT concepts and able to disrupt existing market.
Fields of science
- humanitieslanguages and literaturegeneral language studies
- social sciencesmedia and communicationsgraphic design
- social scienceseconomics and businessbusiness and managementbusiness models
- medical and health sciencesbasic medicineneurologystroke
- natural sciencescomputer and information sciencesartificial intelligencepattern recognition
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