Kairntech platform, for an efficient anonymization.

Data anonymization under GDPR Since the entry into force in 2018 of the General Data Protection Regulation (GDPR), companies must redouble their vigilance with regard to the dissemination of internal documents containing personal data, whether it is data from employees, customers or any other natural person. Article 35 of the Regulation requires them to produce … Continue reading Kairntech platform, for an efficient anonymization.

Kairntech will exhibit at Big Data World Paris, November 27-28, 2019.

Meet us at Big Data World, Paris. For the launch of Big Data World in Paris, the show dedicated to data and Artificial Intelligence, come hear about Data, AI and Innovation like never before and discover the Kairntech Sherpa platform, or how to exploit your unstructured text with Machine Learning and Wikidata. Meet us at booth A82 … Continue reading Kairntech will exhibit at Big Data World Paris, November 27-28, 2019.

Combining state of the art NLP and AI approaches for document analysis.

Introduction A lot of key processes in today's business world involve the analysis and the processing of textual information. For these processes it is good news that today a wide variety of serious NLP components are available, many of them in the public domain. We'll sketch a scenario for a sample analysis task and how … Continue reading Combining state of the art NLP and AI approaches for document analysis.

Kairntech was born in Jan. 2019 to democratize and accelerate NLP solutions at scale.

A ML Engineering platform Kairntech was founded in January 2019 by a team of engineers specializing in artificial intelligence, NLP and software development. Providing a Machine Learning Engineering Platform based on cutting edge open source components and dedicated to unstructured text, Kairntech supports key accounts, administrations, content providers and startups in the implementation and deployment … Continue reading Kairntech was born in Jan. 2019 to democratize and accelerate NLP solutions at scale.