We have data on 30 companies that use textacy. The companies using textacy are most often found in United States and in the Information Technology and Services industry. textacy is most often used by companies with >10000 employees and >1000M dollars in revenue. Our data for textacy usage goes back as far as 5 years and 9 months.
If you’re interested in the companies that use textacy, you may want to check out Google Translate API and MXNet as well.
Company | Istanbul Bilgi University |
Website | bilgi.edu.tr |
Country | Turkey |
Revenue | 200M-1000M |
Company Size | 1000-5000 |
Company | Moser Consulting, Inc. |
Website | moserit.com |
Country | United States |
Revenue | 10M-50M |
Company Size | 200-500 |
Company | Data Science Retreat |
Website | datascienceretreat.com |
Country | Germany |
Revenue | 1M-10M |
Company Size | 10-50 |
Company | Pollen, Inc. |
Website | c2fo.com |
Country | United States |
Revenue | 10M-50M |
Company Size | 500-1000 |
Company | Natixis SA |
Website | natixis.com |
Country | France |
Revenue | >1000M |
Company Size | >10000 |
Company | Website | Country | Revenue | Company Size |
---|---|---|---|---|
Istanbul Bilgi University | bilgi.edu.tr | Turkey | 200M-1000M | 1000-5000 |
Moser Consulting, Inc. | moserit.com | United States | 10M-50M | 200-500 |
Data Science Retreat | datascienceretreat.com | Germany | 1M-10M | 10-50 |
Pollen, Inc. | c2fo.com | United States | 10M-50M | 500-1000 |
Natixis SA | natixis.com | France | >1000M | >10000 |
We use the best indexing techniques combined with advanced data science to monitor the market share of over 15,000 technology products, including Natural Language Processing (NLP). By scanning billions of public documents, we are able to collect deep insights on every company, with over 100 data fields per company at an average. In the Natural Language Processing (NLP) category, textacy has a market share of about 0.1%. Other major and competing products in this category include:
Textacy is a Python library for performing higher-level natural language processing (NLP) tasks, built on the high-performance spaCy library that has tokenization, part-of-speech tagging, dependency parsing, etc. offloaded to another library, textacy focuses on tasks facilitated by the ready availability of tokenized, POS-tagged, and parsed text.
Looking at textacy customers by industry, we find that Information Technology and Services (25%), Higher Education (10%), Computer Software (6%), Professional Training & Coaching (6%) and Financial Services (6%) are the largest segments.
41% of textacy customers are in United States, 21% are in United Kingdom, 6% are in France and 6% are in India.
Of all the customers that are using textacy, 17% are small (<50 employees), 8% are medium-sized and 43% are large (>1000 employees).
Of all the customers that are using textacy, 33% are small (<$50M), 0% are medium-sized and 36% are large (>$1000M).