MINT.extract
Truly refreshing document digitalisation Unlock the full potential of your documents using machine learning
Total Cost €
0EC-Contrib. €
0Partnership
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0MINT.extract project word cloud
Explore the words cloud of the MINT.extract project. It provides you a very rough idea of what is the project "MINT.extract" about.
Project "MINT.extract" data sheet
The following table provides information about the project.
| Coordinator |
TURICODE AG
Organization address contact info |
| Coordinator Country | Switzerland [CH] |
| Project website | https://turicode.com/ |
| Total cost | 71˙429 € |
| EC max contribution | 50˙000 € (70%) |
| Programme |
1. H2020-EU.3. (PRIORITY 'Societal challenges) 2. H2020-EU.2.3. (INDUSTRIAL LEADERSHIP - Innovation In SMEs) 3. H2020-EU.2.1. (INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies) |
| Code Call | H2020-SMEInst-2018-2020-1 |
| Funding Scheme | SME-1 |
| Starting year | 2019 |
| Duration (year-month-day) | from 2019-02-01 to 2019-05-31 |
Partnership
Take a look of project's partnership.
| # | ||||
|---|---|---|---|---|
| 1 | TURICODE AG | CH (WINTERTHUR) | coordinator | 50˙000.00 |
Map
Project objective
Around 80% of relevant business data is unstructured. To make valuable information from documents available for further analysis, lots of resources are invested in repetitive, time-consuming, error-prone and costly manual work. Efficient alternative solutions could reduce by 90% the time and costs employed in such tasks by any business. Digitization, i.e. transformation of human-readable documents into a digital form, is among the most common factors driving digitalization and a fundamental pre-requisite for automated text and data analytics. Digitization in EU could add €2.5trillions to GDP in 2025 MINT.extract is a disruptive information retrieval engine that delivers incredibly advanced document analysis capabilities, thanks to our innovative own-developed purpose-built document query language and AI based learning system. Using methods of artificial intelligence to transform unstructured documents into structured representations (database, XML…) and to read document elements (text, images, tables) as a human would do, our technology goes beyond current template-based solutions by automating many routine business processes and enables big data by integrating data from documents. We aim to create a generic learning system that can be applied to a diverse set of document types (e.g. insurance policies, purchase orders...) and delivers fully automated results in a quality that is superior to current manual data extraction. With MINT.extract we will help businesses to transform their documents to value: making valuable information accessible for everyone. For our company, Turicode. We estimate that 5 years after Phase 2 completion, MINT.extract will bring us additional revenues of €18,7M (x54 revenues of 2018), allowing us to hire 50 new employees and generate €8,25M accumulated profit, reaching a ROI of 3,13.
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The information about "MINT.EXTRACT" are provided by the European Opendata Portal: CORDIS opendata.