Summary
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.
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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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/854135 |
| Start date: | 01-02-2019 |
| End date: | 31-05-2019 |
| Total budget - Public funding: | 71 429,00 Euro - 50 000,00 Euro |
Cordis data
Original description
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 2025MINT.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.
Status
CLOSEDCall topic
EIC-SMEInst-2018-2020Update Date
27-10-2022
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