Segula bets on NPL technology for data management – infoPLC

The firm is participating in the Emphasis R&D project to create a technology ecosystem to enable companies to extract, understand and structure data that comes from text and voice in an automated way.

The digitization of various business processes means that companies have to manage large amounts of data and information. For this reason, organizations acquire systems to analyze this data to enable them to make better business decisions; although at the same time it can be a big challenge for many organizations.

This is why, according to Segula, 60% of Spanish companies have created a strategic plan for data management, citing the latest report produced by IDC. This study also reveals this 36% of Spanish companies have implemented artificial intelligence and machine learning technologies for proper data management.

Segula Technologies was aware of this fact and decided to participate in a research and development project called Emphasis, which uses artificial intelligence and machine learning technology (machine learning) in natural language processing techniques equipped with language handling, interpretation and manipulation (NPL).

An enterprise ecosystem for natural language manipulation functions

This project is being created with the goal of creating a technology ecosystem through which companies can extract, understand and structure data in an automated way that comes from both text and voice. At the same time, it offers a documentation segmentation service and, from 2021, in cooperation with Vicomtech, a center specialized in digital technology research, Segula Technologies started the development of artificial intelligence for data processing throughout the entire life cycle, from information collection to classification, including other functions such as anonymized information processing to increase the degree of confidentiality of sensitive documentation.

At the same time, the Emphasis project proposes the automation of HelpDesk ticket classification systems for solving incidents in companies. It thus enables to speed up the service of clients or employees and thus prevent the occurrence manager You have to choose a technician who must perform each task. At the same time, the assignment of tasks will be automatic, which reduces the time to solve problems and helps manage technical and business resources.

“This research and development project is completely new in that it provides different management layers of technical support tools without being focused on a specific ERP, allowing us to fill gaps in the software that clients already have. The user needs communication with data collection systems that is more friendly, agile, confidential, secure and analytical. For this reason, when we started working on Emphasis, we considered a line of research focused on using natural language to integrate services such as PoC (proof of concept)” Explain Jorge Martínez Santiago, R&I Manager AI ​​& Industry 4.0 at SEGULA Technologies.

Likewise, Emphasis analyzes audio handling by taking voice patterns and converting them to text. In this sense, Jorge Martínez emphasizes: “There are solutions that cover some aspects of those mentioned, but we are conducting research that allows us to use them in the daily life of companies, reducing some of the weaknesses that these systems present. , such as the need to use large databases to train these models.”

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