PangeaMT is the leading subsidiary by Pangeanic offering AI-powered neural machine translation and technology services, particularly to the banking and financial sectors. It will introduce its AI-powered e-Discovery and Knowledge Engineering proof-of-concept to Bankia, at the event that will take place at Innsomnia on the 30th January.

PangeaMT is focused on meeting the huge demand for Natural Language Processing from businesses: anonymization, e-Discovery and document classification, knowledge engineering, neural machine translation, in digital corporations that handle personal data, use Big Data or need to translate massive amounts of data.

The opportunity to develop and custom build an e-Discovery and Knowledge Engineering proof-of-concept as part of a Natural Language Processing at Bankia is very exciting – Manuel Herranz

Banks, financial institutions, cognitive companies, EU and UN international institutions, as well as small-to-medium-sized enterprise owners, form part of is typical clients. PangeaMT’s proprietary big data-driven neural control system, PangeaBox, is a desktop app that translates documents and fully reconstructs the source format, allowing legal teams to run early analysis on foreign legislation and evaluate the documentation required in international litigation. PangeaBox is also used by translation teams that require a fast machine translation solution.

PangeaMT has been selected as part of Innsomnia’s startup hub in its 2018 program to create a Proof-of-Concept (PoC) to automatically detect any non-standard clauses in the banks’s contracts and automate knowledge discovery of key information from legal documents in a structured manner.

PangeaMT is the leading subsidiary offering AI-powered neural machine translation and technology services, particularly to the banking and financial sectors. PangeaMT is focused on meeting the huge demand for Natural Language Processing from businesses: anonymization, e-Discovery and document classification, knowledge engineering, neural machine translation, in digital corporations that handle personal data, use Big Data or need to translate massive amounts of data. Typical clients are banks and financial institutions, cognitive companies, EU and UN international institutions, and small-to-medium-sized enterprise owners. PangeaMT's proprietary big data-driven neural control system, PangeaBox, is a desktop app that translates documents and fully reconstructs the source format, allowing legal teams to run early analysis on foreign legislation and evaluate the documentation required in international litigation. PangeaBox is also used by translation teams that require a fast machine translation solution. PangeaMT has been selected as part of Innsomnia's startup hub in its 2018 program to create a Proof-of-Concept (PoC) to automatically detect any non-standard clauses in the banks's contracts and automate knowledge discovery of key information from legal documents in a structured manner. The collaboration will establish a strategic partnership with Innsomnia and Bankia in multiple areas of its business operations to directly complement its cutting-edge risk anonymization, summarization, machine translation capabilities.The collaboration will establish a strategic partnership with Innsomnia and Bankia in multiple areas of its business operations to directly complement its cutting-edge risk anonymization, summarization, machine translation capabilities. The main project will start in February and PangeaMT will work on a Knowledge Engineering proof-of-concept for the bank.

PangeaMT is definetely in the right path with the e-Discovery and Knowledge Engineering proof-of-concept for Bankia, and the bank’s support – Amando Estela

 

 

Proof-of-concept for Bankia and bank’s support

Pangeanic’s CEO Manuel Herranz said: “I am very happy to have led such a committed team to this new goal.

Manuel Herranz is PangeaMT's CEO

Manuel Herranz , PangeaMT’s CEO

The opportunity to develop and custom build an e-Discovery and Knowledge Engineering proof-of-concept as part of a Natural Language Processing at Bankia is very exciting. It fits very well with our overall  business strategy to become a leader in AI-powered NLP within the next three years. I am very proud to work at a company whose leadership team clearly understands the important strategic role that the human resources function plays in a company’s growth business strategy.”

Amando Estela, PangeaMT’s CTO “PangeaMT is definetely in the right path with this e-Discovery and Knowledge Engineering proof-of-concept for Bankia, and the bank’s support.

amando estela PangeaMT CTO

Amando Estela, PangeaMT’s CTO

We have searched several funding opportunities and also areas where to best apply our language technologies. Innsomnia was the best one in terms of location, facilities and help to startups. We were impressed from the beginning. The team spirit is really amazing, the interaction of the ecosystem they are building – it makes me smile every day. We are truly getting amazing support and help with Bankia. I’m so happy to be part of such an incredible project.”

About Alexandre

Alexandre joined Pangeanic in 2011 while still finishing his Master’s degree in applied machine translation. Alex attended the University of Alicante where he studied Technical Engineering in Computer Science, with major in pattern recognition. He majored in Machine Translation, Artificial Intelligence, Neural Networks, Pattern Recognition and Digital Imaging during his Master’s Degree at the Polytechnic University of Valencia, where he was also involved in the development of the first version of PangeaMT back in 2010.He is a specialist in Machine Translation in distant languages, like Japanese-English, Chinese-English-Spanish. His daily duties include Research and Development and programming. He is also Pangeanic’s system administrator.In our team, Alex has been responsible for the technical aspects of the research implementation of EU’s EXPERT project at Pangeanic, including search-engine techniques based on Elastic Search in a massive database and hybrid MT + TM approaches.