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Company Name:

COSTIFIER

Incubation Round:

Explore

Application Track:

Track 1

Proposed by:

Track 1

Challenge Name:

Data-Based Optimisation of Manufacturing Processes

Product Description

Fully automated “company-specific” model will be created by Costifier from company’s previous data with machine learning methods. SMEs will use their own model for making highly accurate (> 90%) and fast (1-2 sec) cost and machining time estimations. Costifier will makes cost estimation by calculating the similarity of new products to already manufactured parts using machine learning methods. In addition, it will be possible to increase productivity up to 15% by running “tailor-made” models for more cost-effective manufacturing alternatives.

Usage of Standards for data interoperability:

Costifier uses standard API’s for both data input as well as output. APIs are compliant with all best practices.

*Expose phase is open to all Experiment phase teams

Location:

Ankara, Turkey

Sector:

Manufacturing / Industry

Website:

https://www.costifier.com

Company maturity:

Pre-MVP and MVP

Investment level:

Seed

Funding raised:

< EUR 500,000

Collaboration opportunity:

Marketing, Distribution, Service / Support, Investment

Company Description

Costifier is a spinoff project of SFM YAZILIM TEKNOLOJILERI A.S. (“SFM”) which is a technology start-up company working on machine learning methods for manufacturing industry problems. SFM was founded in May 2019. The main purpose of the company is to create economical solutions for fundamental problems in the manufacturing industry. SFM focuses on the cost-effective solutions that can be applied to manufacturing SMEs by machine learning algorithms, such as cost estimation for bidding. SFM’s vision is to be the one of pioneer machine learning software company in manufacturing industry.

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The DIH TERA consortium consists of organisations based in East Croatia, among which there are constituents of the two East Croatian universities and development agencies from all five of the region’s counties, as well as business support institutions and renowned Croatian SMEs with extensive knowledge and experience in the IT sector and digitalisation processes. The coordinator is an SME with a not-for-profit clause, established by the Josip Juraj Strossmayer University of Osijek, Osijek-Baranja County and the City of Osijek.

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The Centre for Research and Technology Hellas is one of the largest research centres in Greece; top 1 in north Greece. It was founded in 2000 and is located in Thessaloniki. Its mission is to promote the triplet Research – Development – Innovation by conducting high quality research and developing innovative products and services while building strong partnerships with industry and strategic collaborations with academia and other research and technology organisations in Greece and abroad.

EstBAN is an organization for business angels and business angel groups seeking investment opportunities in Estonia and its neighbouring regions with an aim to grow the quantity and quality of local seed stage investments. In 2014, EstBAN was awarded “The Best Newcomer in Europe” by European Business Angels network and in 2018 received an award for the Best Early Stage Ecosystem and performing EBAN member. As of 2019, EstBAN has 150+ members that invested a total of €7 million EUR during 2018. EstBAN’s main aim is to increase the amount of angel investments in Estonian startup ecosystem, support and train angel investors to become more knowledgeable, improve the deal flow quality and raise the number of angel investors in EstBAN.

Gnúbila is a data privacy solution designer and independent software vendor. GNúbila provides solutions to extract, de-identify, demilitarise and share medical sensitive data cross-enterprise and transnationally. Actively supporting European and international consortia since a decade, Gnúbila justifies a rich experience in the field of biomedical research and e-health big data platforms developments. Its goal is to offer state-of-the- art anonymisation techniques to process all possible medical information and make it shareable in big data scenarios. Gnúbila enforces privacy and informational self-determination by design.

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