Companies that use Spark NLP

Frequently asked questions

What is the source of this data?

Our data is sourced from job postings collected from millions of companies. We monitor these postings on company websites, job boards, and other recruitment platforms. Analyzing job postings provides a reliable method to understand the technologies companies are employing, including their use of internal tools.

How often is the data updated?

We refresh our data daily to ensure you are accessing the most current information available. This frequent updating process guarantees that our insights and intelligence reflect the latest developments and trends within the industry.

What is Spark NLP?

Spark NLP is a cutting-edge natural language processing (NLP) library built on Apache Spark and developed by John Snow Labs. It offers state-of-the-art performance for processing and analyzing human language data. Spark NLP provides a wide range of tools and utilities that enable businesses and data scientists to extract valuable insights from text data efficiently.

NLP/Sentiment Analysis is the category in which Spark NLP operates. This field focuses on understanding and interpreting human language text, allowing for sentiment analysis, text classification, named entity recognition, and other language-related tasks. Spark NLP stands out in this category due to its scalability, speed, and comprehensive set of pre-trained models that cover multiple languages and domains.

Founded in 2016 by the team at John Snow Labs, Spark NLP was created with the goal of democratizing access to advanced NLP capabilities. The motivation behind the development of Spark NLP was to address the growing need for robust and scalable NLP tools that could handle large volumes of text data effectively. Since its inception, Spark NLP has gained significant traction in the industry and has become a popular choice for organizations looking to leverage NLP technology.

Currently, Spark NLP holds a notable market share within the NLP/Sentiment Analysis category. With a focus on performance and ease of use, Spark NLP is projected to continue its growth trajectory in the future. As the demand for sophisticated NLP solutions increases across various industries, Spark NLP is well-positioned to expand its market share and solidify its position as a leading technology in the field of natural language processing.

How to get an updated list of companies that use Spark NLP?

You can access an updated list of companies using Spark NLP by visiting TheirStack.com. Our platform provides a comprehensive database of companies utilizing various technologies and internal tools.

How many customers does Spark NLP have?

As of now, we have data on 83 companies that use Spark NLP.

Who uses Spark NLP?

Spark NLP is used by a diverse range of organizations across various industries, including "Retail Apparel And Fashion", "It Services And It Consulting", "It Services And It Consulting", "Business Consulting And Services", "Hospitals And Health Care", "Professional Services", "It Services And It Consulting", "Business Consulting And Services", "Advertising Services". For a comprehensive list of all industries utilizing Spark NLP, please visit TheirStack.com.

What companies use Spark NLP?

Some of the companies that use Spark NLP include Poshmark, Planned Systems International, John Snow Labs, Lovelytics, CVS Health, Leibniz-Gemeinschaft, OLX Group, ANALTYTICA, EXL, Team Go and many more. You can find a complete list of 83 companies that use Spark NLP on TheirStack.com.

In which countries Spark NLP is used the most?

Based on our data, Spark NLP is most popular in United States (40 companies), United Kingdom (5 companies), France (4 companies), Poland (4 companies), India (3 companies), Netherlands (2 companies), Switzerland (2 companies), Afghanistan (1 companies), Germany (1 companies), Japan (1 companies). However, it is used by companies all over the world.

How to find companies that use Spark NLP?

You can find companies using Spark NLP by searching for it on TheirStack.com, We track job postings from millions of companies and use them to discover what technologies and internal tools they are using.