NLP And Text Analytics

Gain market share and customer base information about the top NLP And Text Analytics software. Check out our list of NLP And Text Analytics Software, analyze them by marketshare, region, company size along with information about competitors, prospects, tech stacks, funding information, contract renewal dates and more.

58

Technologies Tracked

13083

Companies Tracked

Categories related to NLP And Text Analytics

Data Integration
Artificial Intelligence
Backup And Recovery
Data Visualization
Analytics And BI Platform

Top 5 NLP And Text Analytics technologies in 2026

Over 13083 companies are using NLP And Text Analytics tools. Hugging Face with 41.66% market share (5451 customers), GitHub Copilot with 25.06% market share (3278 customers), Microsoft Azure Speech to Text with 3.88% market share (507 customers).

Technology

Market Share (Est.)

Customers

  • Hugging Face

    41.66%

    5451

  • GitHub Copilot

    25.06%

    3278

  • Microsoft Azure Speech to Text

    3.88%

    507

  • Azure Translator

    3.73%

    488

  • IBM Watson Assistant

    3.58%

    469

  • Others

    22.09%

    2890

  • NLP And Text Analytics Customers by Employee Size

    The majority of NLP And Text Analytics category falls in the company size of 10,000+ employees (2927 companies), 100 - 249 employees (2521 companies), 1,000 - 4,999 employees (1923 companies).

    Employee Size

    NLP And Text Analytics Customers by Geography

    Companies using NLP And Text Analytics technology software are majorly from the United States with 5775 (56.67%), India with 1142 (11.21%), United Kingdom with 727 (7.13%) customers respectively.

    Customers

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    NLP And Text Analytics Customers by Industry

    Top industries that use NLP And Text Analytics for Artificial Intelligence (691), Machine Learning (633), Cloud Services (549).

    Customers

    Market Share for Top NLP And Text Analytics Technologies

    Analyze the market share of popular NLP And Text Analytics technologies along with information about competitors, prospects, tech stacks, funding information, contract renewal dates and more

    Ranking
    Technology
    Customers
    Market share(Est.)(%)
    1Hugging Face545141.66
    2GitHub Copilot327825.06
    3Microsoft Azure Speech to Text5073.88
    4Azure Translator4883.73
    5IBM Watson Assistant4693.58
    6Dragon NaturallySpeaking4363.33
    7Google Cloud Speech-to-Text3202.45
    8Cohere3202.45
    9Azure Language Understanding3112.38
    10Google Cloud Text-to-Speech1771.35
    11Azure QnA Maker1761.35
    12Wit.ai1731.32
    13Sinequa1351.03
    14Google Cloud Natural Language API850.65
    15AllegroGraph720.55
    16SoundHound580.44
    17Oracle InQuira540.41
    18Expert.ai490.37
    19IBM Watson Speech-to-Text440.34
    20IBM Watson Knowledge Studio430.33
    21IBM Watson Content Analytics400.31
    22ABBYY Vantage360.28
    23Apache cTAKES270.21
    24Nuance Recognizer270.21
    25Verint Text Analytics270.21
    26Iris.ai270.21
    27Herbie.ai190.15
    28Cloudmersive180.14
    29IBM Watson Tone Analyzer170.13
    30Relative Insight170.13
    31Amazon Comprehend Medical160.12
    32Bitext150.11
    33Lettria140.11
    34SAS Contextual Analysis140.11
    35Kimola Cognitive130.10
    36Aylien100.08
    37HumanFirst90.07
    38Tisane80.06
    39Gavagai80.06
    40deepset.ai80.06
    41Nuance Text to Speech70.05
    42TextRazor70.05
    43Celebros Search50.04
    44MeaningCloud50.04
    45Arria NLG Studio50.04
    46NLSQL50.04
    47Nuance SpeechMagic40.03
    48Nuance Transcend40.03
    49Pangeanic40.03
    50Nuance RadWhere30.02
    51DeepScribe30.02
    52Lymba30.02
    53Nuance Editscript20.02
    54Nuance Nina20.02
    55ChatSonic by Writesonic20.02
    56Symbl20.02
    57DataChat20.02
    58Vyntelligence20.02

    FAQ

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    Who are the top NLP And Text Analytics software market leaders?

    Top leaders in the category for NLP And Text Analytics software are Hugging Face, GitHub Copilot, Microsoft Azure Speech to Text. Here, you can view a full list of NLP And Text Analytics tools in the market.

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