English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

As the use of technology increases and data analysis becomes integral in manybusinesses, the ability to quickly access and interpret data has become moreimportant than ever. Information retrieval technologies are being utilized byorganizations and companies to manage their information systems and processes.Despite information retrieval of a large amount of data being efficientorganized in relational databases, a user still needs to master the DBlanguage/schema to completely formulate the queries. This puts a burden onorganizations and companies to hire employees that are proficient in DBlanguages/schemas to formulate queries. To reduce some of the burden on alreadyoverstretched data teams, many organizations are looking for tools that allownon-developers to query their databases. Unfortunately, writing a valid SQLquery that answers the question a user is trying to ask isn't always easy. Evenseemingly simple questions, like "Which start-up companies received more than$200M in funding?" can actually be very hard to answer, let alone convert intoa SQL query. How do you define start-up companies? By size, location, durationof time they have been incorporated? This may be fine if a user is working witha database they're already familiar with, but what if users are not familiarwith the database. What is needed is a centralized system that can effectivelytranslate natural language queries into specific database queries for differentcustomer database types. There is a number of factors that can dramaticallyaffect the system architecture and the set of algorithms used to translate NLqueries into a structured query representation.

Pragmatic approach to structured data querying via natural language interface