What are our data sources?
We use the data sources on the side for ranking solutions and awarding badges in natural language understanding (nlu) software category. Our data sources in natural language understanding (nlu) software category include;
Natural language understanding (NLU) Software are tools that leverage natural language processing and understanding to comprehend human speech and perform tasks accordingly.
NLU software is used in different business applications such as chatbots, virtual assistants, SEO monitoring, web crawling, machine translation, emotion and sentiment detection, and automatic summarization, among other NLP use cases.
If you’d like to learn about the ecosystem consisting of Natural Language Understanding (NLU) Software and others, feel free to check AIMultiple Conversational AI.
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We use the data sources on the side for ranking solutions and awarding badges in natural language understanding (nlu) software category. Our data sources in natural language understanding (nlu) software category include;
review websites
social media websites
search engine data for branded queries
According to the weighted combination of 7 data sources
Kapiche
MonkeyLearn
Relative Insight
Inbenta
Microsoft Knowledge Exploration Service
Taking into account the latest metrics outlined below, these are the current natural language understanding (nlu) software market leaders. Market leaders are not the overall leaders since market leadership doesn’t take into account growth rate.
Microsoft Knowledge Exploration Service
Kapiche
NLTK
Relative Insight
MonkeyLearn
These are the number of queries on search engines which include the brand name of the solution. Compared to other Conversational AI categories, Natural Language Understanding (NLU) Software is more concentrated in terms of top 3 companies’ share of search queries. Top 3 companies receive 46%, 30% more than the average of search queries in this area.
281 employees work for a typical company in this solution category which is 260 more than the number of employees for a typical company in the average solution category.
In most cases, companies need at least 10 employees to serve other businesses with a proven tech product or service. 34 companies with >10 employees are offering natural language understanding (nlu) software. Top 3 products are developed by companies with a total of 400k employees. The largest company building natural language understanding (nlu) software is IBM with more than 300,000 employees.
Taking into account the latest metrics outlined below, these are the fastest growing solutions:
Kapiche
MonkeyLearn
Inbenta
Relative Insight
Wordsmith
We have analyzed reviews published in the last months. These were published in 4 review platforms as well as vendor websites where the vendor had provided a testimonial from a client whom we could connect to a real person.
These solutions have the best combination of high ratings from reviews and number of reviews when we take into account all their recent reviews.
This data is collected from customer reviews for all Natural Language Understanding (NLU) Software companies. The most positive word describing Natural Language Understanding (NLU) Software is “Easy to use” that is used in 11% of the reviews. The most negative one is “Difficult” with which is used in 5.00% of all the Natural Language Understanding (NLU) Software reviews.
According to customer reviews, most common company size for natural language understanding (nlu) software customers is 1-50 Employees. Customers with 1-50 Employees make up 42% of natural language understanding (nlu) software customers. For an average Conversational AI solution, customers with 1-50 Employees make up 41% of total customers.
These scores are the average scores collected from customer reviews for all Natural Language Understanding (NLU) Software. Natural Language Understanding (NLU) Software is most positively evaluated in terms of "Customer Service" but falls behind in "Ease of Use".
This category was searched on average for 43 times per month on search engines in 2022. This number has decreased to 40 in 2023. If we compare with other conversational ai solutions, a typical solution was searched 814 times in 2022 and this decreased to 720 in 2023.