Best Natural Language Understanding (NLU) Software

Matthew Miller
MM
Researched and written by Matthew Miller

Natural language understanding (NLU), a form of natural language processing (NLP), allows users to better understand text through machine learning algorithms and statistical methods. These algorithms take language as an input and provide a variety of outputs based on the required task, including part-of-speech tagging, automatic summarization, Named Entity Recognition, sentiment analysis, emotion detection, parsing, tokenization, lemmatization, language detection, and more.

Some example use cases include chatbots, translation applications, and social media monitoring tools that scan Facebook and Twitter for mentions. NLU algorithms are an example of a deep learning algorithm and may be a prebuilt offering in an AI platform.

To qualify for inclusion in the Natural Language Understanding category, a product must:

Provide a deep learning algorithm specifically for human language interaction
Connect with language data pools to learn a specific solution or function
Consume the language as an input and provide an outputted solution

Best Natural Language Understanding (NLU) Software At A Glance

Best for Small Businesses:
Best for Mid-Market:
Best for Enterprise:
Highest User Satisfaction:
Best Free Software:
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Highest User Satisfaction:
Best Free Software:

G2 takes pride in showing unbiased reviews on user satisfaction in our ratings and reports. We do not allow paid placements in any of our ratings, rankings, or reports. Learn about our scoring methodologies.

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48 Listings in Natural Language Understanding (NLU) Available
(292)4.4 out of 5
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  • Overview
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  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    Make your content and apps multilingual with fast, dynamic machine translation available in thousands of language pairs.

    Users
    • Software Engineer
    • Data Engineer
    Industries
    • Information Technology and Services
    • Computer Software
    Market Segment
    • 50% Small-Business
    • 26% Enterprise
  • Pros and Cons
    Expand/Collapse Pros and Cons
  • Google Cloud Translation API Pros and Cons
    How are these determined?Information
    Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
    Pros
    Translation Services
    150
    Ease of Use
    148
    Language Support
    91
    Multilingual Support
    91
    Fast Translation
    81
    Cons
    Translation Accuracy
    77
    Accuracy Issues
    52
    Expensive
    39
    Language Support
    39
    Translation Limitations
    39
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • Google Cloud Translation API features and usability ratings that predict user satisfaction
    8.8
    Summarization
    Average: 8.9
    8.8
    Language Detection
    Average: 8.8
    8.8
    Part of Speech Tagging
    Average: 8.7
    8.5
    Quality of Support
    Average: 8.3
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Seller
    Google
    Company Website
    Year Founded
    1998
    HQ Location
    Mountain View, CA
    Twitter
    @google
    32,136,453 Twitter followers
    LinkedIn® Page
    www.linkedin.com
    302,978 employees on LinkedIn®
Product Description
How are these determined?Information
This description is provided by the seller.

Make your content and apps multilingual with fast, dynamic machine translation available in thousands of language pairs.

Users
  • Software Engineer
  • Data Engineer
Industries
  • Information Technology and Services
  • Computer Software
Market Segment
  • 50% Small-Business
  • 26% Enterprise
Google Cloud Translation API Pros and Cons
How are these determined?Information
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Pros
Translation Services
150
Ease of Use
148
Language Support
91
Multilingual Support
91
Fast Translation
81
Cons
Translation Accuracy
77
Accuracy Issues
52
Expensive
39
Language Support
39
Translation Limitations
39
Google Cloud Translation API features and usability ratings that predict user satisfaction
8.8
Summarization
Average: 8.9
8.8
Language Detection
Average: 8.8
8.8
Part of Speech Tagging
Average: 8.7
8.5
Quality of Support
Average: 8.3
Seller Details
Seller
Google
Company Website
Year Founded
1998
HQ Location
Mountain View, CA
Twitter
@google
32,136,453 Twitter followers
LinkedIn® Page
www.linkedin.com
302,978 employees on LinkedIn®
(103)4.3 out of 5
1st Easiest To Use in Natural Language Understanding (NLU) software
View top Consulting Services for Google Cloud Natural Language API
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Entry Level Price:Free
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    Derive insights from unstructured text using Google machine learning.

    Users
    • Software Engineer
    Industries
    • Computer Software
    • Information Technology and Services
    Market Segment
    • 51% Small-Business
    • 20% Enterprise
  • Pros and Cons
    Expand/Collapse Pros and Cons
  • Google Cloud Natural Language API Pros and Cons
    How are these determined?Information
    Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
    Pros
    Ease of Use
    41
    NLP Capabilities
    41
    Accuracy
    26
    Natural Language Processing
    24
    Sentiment Analysis
    24
    Cons
    Expensive
    16
    Limited Language Support
    8
    Poor Documentation
    7
    Limitations
    6
    Pricing Issues
    6
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • Google Cloud Natural Language API features and usability ratings that predict user satisfaction
    8.6
    Summarization
    Average: 8.9
    8.8
    Language Detection
    Average: 8.8
    8.6
    Part of Speech Tagging
    Average: 8.7
    8.6
    Quality of Support
    Average: 8.3
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Seller
    Google
    Company Website
    Year Founded
    1998
    HQ Location
    Mountain View, CA
    Twitter
    @google
    32,136,453 Twitter followers
    LinkedIn® Page
    www.linkedin.com
    302,978 employees on LinkedIn®
Product Description
How are these determined?Information
This description is provided by the seller.

Derive insights from unstructured text using Google machine learning.

Users
  • Software Engineer
Industries
  • Computer Software
  • Information Technology and Services
Market Segment
  • 51% Small-Business
  • 20% Enterprise
Google Cloud Natural Language API Pros and Cons
How are these determined?Information
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Pros
Ease of Use
41
NLP Capabilities
41
Accuracy
26
Natural Language Processing
24
Sentiment Analysis
24
Cons
Expensive
16
Limited Language Support
8
Poor Documentation
7
Limitations
6
Pricing Issues
6
Google Cloud Natural Language API features and usability ratings that predict user satisfaction
8.6
Summarization
Average: 8.9
8.8
Language Detection
Average: 8.8
8.6
Part of Speech Tagging
Average: 8.7
8.6
Quality of Support
Average: 8.3
Seller Details
Seller
Google
Company Website
Year Founded
1998
HQ Location
Mountain View, CA
Twitter
@google
32,136,453 Twitter followers
LinkedIn® Page
www.linkedin.com
302,978 employees on LinkedIn®

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(146)4.3 out of 5
2nd Easiest To Use in Natural Language Understanding (NLU) software
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  • Overview
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  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    Experience the state-of-the-art performance of Llama 3, an openly accessible model that excels at language nuances, contextual understanding, and complex tasks like translation and dialogue generation

    Users
    • Software Engineer
    Industries
    • Computer Software
    • Information Technology and Services
    Market Segment
    • 58% Small-Business
    • 24% Mid-Market
  • Pros and Cons
    Expand/Collapse Pros and Cons
  • Meta Llama 3 Pros and Cons
    How are these determined?Information
    Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
    Pros
    Accuracy
    36
    Ease of Use
    29
    Speed
    29
    Open-Source
    25
    Helpful
    22
    Cons
    Limitations
    26
    Slow Performance
    17
    Poor Response Quality
    16
    Inaccuracy
    13
    Limited Understanding
    11
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • Meta Llama 3 features and usability ratings that predict user satisfaction
    8.7
    Summarization
    Average: 8.9
    8.4
    Language Detection
    Average: 8.8
    7.6
    Part of Speech Tagging
    Average: 8.7
    7.1
    Quality of Support
    Average: 8.3
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Year Founded
    2008
    HQ Location
    Menlo Park, CA
    Twitter
    @Meta
    13,755,247 Twitter followers
    LinkedIn® Page
    www.linkedin.com
    119,009 employees on LinkedIn®
    Ownership
    NASDAQ: META
Product Description
How are these determined?Information
This description is provided by the seller.

Experience the state-of-the-art performance of Llama 3, an openly accessible model that excels at language nuances, contextual understanding, and complex tasks like translation and dialogue generation

Users
  • Software Engineer
Industries
  • Computer Software
  • Information Technology and Services
Market Segment
  • 58% Small-Business
  • 24% Mid-Market
Meta Llama 3 Pros and Cons
How are these determined?Information
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Pros
Accuracy
36
Ease of Use
29
Speed
29
Open-Source
25
Helpful
22
Cons
Limitations
26
Slow Performance
17
Poor Response Quality
16
Inaccuracy
13
Limited Understanding
11
Meta Llama 3 features and usability ratings that predict user satisfaction
8.7
Summarization
Average: 8.9
8.4
Language Detection
Average: 8.8
7.6
Part of Speech Tagging
Average: 8.7
7.1
Quality of Support
Average: 8.3
Seller Details
Year Founded
2008
HQ Location
Menlo Park, CA
Twitter
@Meta
13,755,247 Twitter followers
LinkedIn® Page
www.linkedin.com
119,009 employees on LinkedIn®
Ownership
NASDAQ: META
(77)4.3 out of 5
3rd Easiest To Use in Natural Language Understanding (NLU) software
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  • Overview
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  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    Azure AI Language is a managed service for developing natural language processing applications. Identify key terms and phrases, analyze sentiment, summarize text, and build conversational interfaces.

    Users
    No information available
    Industries
    No information available
    Market Segment
    • 42% Small-Business
    • 32% Enterprise
  • Pros and Cons
    Expand/Collapse Pros and Cons
  • Azure AI Language Pros and Cons
    How are these determined?Information
    Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
    Pros
    Natural Language Processing
    8
    Understanding
    8
    Customization
    7
    Ease of Use
    7
    Integrations
    7
    Cons
    Expensive
    5
    Difficult Learning
    3
    Limitations
    3
    Limited Language Support
    3
    Poor Customer Support
    3
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • Azure AI Language features and usability ratings that predict user satisfaction
    8.2
    Summarization
    Average: 8.9
    8.5
    Language Detection
    Average: 8.8
    8.1
    Part of Speech Tagging
    Average: 8.7
    8.4
    Quality of Support
    Average: 8.3
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Seller
    Microsoft
    Year Founded
    1975
    HQ Location
    Redmond, Washington
    Twitter
    @microsoft
    13,938,794 Twitter followers
    LinkedIn® Page
    www.linkedin.com
    244,190 employees on LinkedIn®
    Ownership
    MSFT
Product Description
How are these determined?Information
This description is provided by the seller.

Azure AI Language is a managed service for developing natural language processing applications. Identify key terms and phrases, analyze sentiment, summarize text, and build conversational interfaces.

Users
No information available
Industries
No information available
Market Segment
  • 42% Small-Business
  • 32% Enterprise
Azure AI Language Pros and Cons
How are these determined?Information
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Pros
Natural Language Processing
8
Understanding
8
Customization
7
Ease of Use
7
Integrations
7
Cons
Expensive
5
Difficult Learning
3
Limitations
3
Limited Language Support
3
Poor Customer Support
3
Azure AI Language features and usability ratings that predict user satisfaction
8.2
Summarization
Average: 8.9
8.5
Language Detection
Average: 8.8
8.1
Part of Speech Tagging
Average: 8.7
8.4
Quality of Support
Average: 8.3
Seller Details
Seller
Microsoft
Year Founded
1975
HQ Location
Redmond, Washington
Twitter
@microsoft
13,938,794 Twitter followers
LinkedIn® Page
www.linkedin.com
244,190 employees on LinkedIn®
Ownership
MSFT
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    Amazon Comprehend is a natural language processing (NLP) service that uses machine learning to find insights and relationships in text. Amazon Comprehend identifies the language of the text; extracts

    Users
    No information available
    Industries
    • Information Technology and Services
    • Computer Software
    Market Segment
    • 39% Mid-Market
    • 38% Small-Business
  • Pros and Cons
    Expand/Collapse Pros and Cons
  • Amazon Comprehend Pros and Cons
    How are these determined?Information
    Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
    Pros
    Ease of Use
    5
    Sentiment Analysis
    4
    Accuracy
    3
    Integrations
    3
    Automation
    2
    Cons
    Expensive
    4
    Inaccuracy
    3
    Steep Learning Curve
    3
    Subscription Cost
    3
    Data Privacy
    2
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • Amazon Comprehend features and usability ratings that predict user satisfaction
    8.6
    Summarization
    Average: 8.9
    8.3
    Language Detection
    Average: 8.8
    8.7
    Part of Speech Tagging
    Average: 8.7
    8.4
    Quality of Support
    Average: 8.3
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Year Founded
    2006
    HQ Location
    Seattle, WA
    Twitter
    @awscloud
    2,221,081 Twitter followers
    LinkedIn® Page
    www.linkedin.com
    136,383 employees on LinkedIn®
    Ownership
    NASDAQ: AMZN
Product Description
How are these determined?Information
This description is provided by the seller.

Amazon Comprehend is a natural language processing (NLP) service that uses machine learning to find insights and relationships in text. Amazon Comprehend identifies the language of the text; extracts

Users
No information available
Industries
  • Information Technology and Services
  • Computer Software
Market Segment
  • 39% Mid-Market
  • 38% Small-Business
Amazon Comprehend Pros and Cons
How are these determined?Information
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Pros
Ease of Use
5
Sentiment Analysis
4
Accuracy
3
Integrations
3
Automation
2
Cons
Expensive
4
Inaccuracy
3
Steep Learning Curve
3
Subscription Cost
3
Data Privacy
2
Amazon Comprehend features and usability ratings that predict user satisfaction
8.6
Summarization
Average: 8.9
8.3
Language Detection
Average: 8.8
8.7
Part of Speech Tagging
Average: 8.7
8.4
Quality of Support
Average: 8.3
Seller Details
Year Founded
2006
HQ Location
Seattle, WA
Twitter
@awscloud
2,221,081 Twitter followers
LinkedIn® Page
www.linkedin.com
136,383 employees on LinkedIn®
Ownership
NASDAQ: AMZN
(15)4.5 out of 5
View top Consulting Services for Google Cloud AutoML Natural Language
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  • Overview
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  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    The powerful pre-trained models of the Natural Language API let developers work with natural language understanding features including sentiment analysis, entity analysis, entity sentiment analysis, c

    Users
    No information available
    Industries
    No information available
    Market Segment
    • 53% Small-Business
    • 27% Enterprise
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • Google Cloud AutoML Natural Language features and usability ratings that predict user satisfaction
    9.4
    Summarization
    Average: 8.9
    8.3
    Language Detection
    Average: 8.8
    8.6
    Part of Speech Tagging
    Average: 8.7
    8.5
    Quality of Support
    Average: 8.3
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Seller
    Google
    Year Founded
    1998
    HQ Location
    Mountain View, CA
    Twitter
    @google
    32,136,453 Twitter followers
    LinkedIn® Page
    www.linkedin.com
    302,978 employees on LinkedIn®
    Ownership
    NASDAQ:GOOG
Product Description
How are these determined?Information
This description is provided by the seller.

The powerful pre-trained models of the Natural Language API let developers work with natural language understanding features including sentiment analysis, entity analysis, entity sentiment analysis, c

Users
No information available
Industries
No information available
Market Segment
  • 53% Small-Business
  • 27% Enterprise
Google Cloud AutoML Natural Language features and usability ratings that predict user satisfaction
9.4
Summarization
Average: 8.9
8.3
Language Detection
Average: 8.8
8.6
Part of Speech Tagging
Average: 8.7
8.5
Quality of Support
Average: 8.3
Seller Details
Seller
Google
Year Founded
1998
HQ Location
Mountain View, CA
Twitter
@google
32,136,453 Twitter followers
LinkedIn® Page
www.linkedin.com
302,978 employees on LinkedIn®
Ownership
NASDAQ:GOOG
By IBM
(34)4.2 out of 5
4th Easiest To Use in Natural Language Understanding (NLU) software
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  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    Analyze text to extract meta-data from content such as concepts, entities, keywords, categories, relations and semantic roles.

    Users
    No information available
    Industries
    • Information Technology and Services
    • Computer Software
    Market Segment
    • 56% Small-Business
    • 26% Enterprise
  • Pros and Cons
    Expand/Collapse Pros and Cons
  • IBM Watson Natural Language Understanding Pros and Cons
    How are these determined?Information
    Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
    Pros
    Ease of Use
    8
    Accuracy
    4
    User Interface
    4
    Customization
    3
    Functionality
    3
    Cons
    Complex Setup
    4
    Complexity
    1
    Difficult Learning
    1
    Limitations
    1
    Not User-Friendly
    1
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • IBM Watson Natural Language Understanding features and usability ratings that predict user satisfaction
    7.4
    Summarization
    Average: 8.9
    8.2
    Language Detection
    Average: 8.8
    8.5
    Part of Speech Tagging
    Average: 8.7
    7.7
    Quality of Support
    Average: 8.3
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Seller
    IBM
    Year Founded
    1911
    HQ Location
    Armonk, NY
    Twitter
    @IBM
    714,459 Twitter followers
    LinkedIn® Page
    www.linkedin.com
    317,108 employees on LinkedIn®
    Ownership
    SWX:IBM
Product Description
How are these determined?Information
This description is provided by the seller.

Analyze text to extract meta-data from content such as concepts, entities, keywords, categories, relations and semantic roles.

Users
No information available
Industries
  • Information Technology and Services
  • Computer Software
Market Segment
  • 56% Small-Business
  • 26% Enterprise
IBM Watson Natural Language Understanding Pros and Cons
How are these determined?Information
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Pros
Ease of Use
8
Accuracy
4
User Interface
4
Customization
3
Functionality
3
Cons
Complex Setup
4
Complexity
1
Difficult Learning
1
Limitations
1
Not User-Friendly
1
IBM Watson Natural Language Understanding features and usability ratings that predict user satisfaction
7.4
Summarization
Average: 8.9
8.2
Language Detection
Average: 8.8
8.5
Part of Speech Tagging
Average: 8.7
7.7
Quality of Support
Average: 8.3
Seller Details
Seller
IBM
Year Founded
1911
HQ Location
Armonk, NY
Twitter
@IBM
714,459 Twitter followers
LinkedIn® Page
www.linkedin.com
317,108 employees on LinkedIn®
Ownership
SWX:IBM
(319)4.7 out of 5
6th Easiest To Use in Natural Language Understanding (NLU) software
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  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    InMoment, the leader in improving experiences and the highest recommended CX platform and services company in the world is renowned for helping clients collect and integrate customer experience data t

    Users
    • Product Manager
    • Customer Success Manager
    Industries
    • Computer Software
    • Information Technology and Services
    Market Segment
    • 47% Small-Business
    • 39% Mid-Market
  • Pros and Cons
    Expand/Collapse Pros and Cons
  • InMoment Experience Improvement (XI) Platform Pros and Cons
    How are these determined?Information
    Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
    Pros
    Customer Feedback
    5
    Feedback Management
    5
    Helpful
    5
    Data Management
    3
    Ease of Use
    3
    Cons
    Filtering Issues
    3
    AI Limitations
    2
    Difficult Reporting
    2
    Expensive
    2
    Limitations
    2
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • InMoment Experience Improvement (XI) Platform features and usability ratings that predict user satisfaction
    0.0
    No information available
    0.0
    No information available
    0.0
    No information available
    9.0
    Quality of Support
    Average: 8.3
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Seller
    InMoment
    Year Founded
    2002
    HQ Location
    Salt Lake City, UT
    Twitter
    @WeAreInMoment
    1,945 Twitter followers
    LinkedIn® Page
    www.linkedin.com
    745 employees on LinkedIn®
    Phone
    905-542-9001
Product Description
How are these determined?Information
This description is provided by the seller.

InMoment, the leader in improving experiences and the highest recommended CX platform and services company in the world is renowned for helping clients collect and integrate customer experience data t

Users
  • Product Manager
  • Customer Success Manager
Industries
  • Computer Software
  • Information Technology and Services
Market Segment
  • 47% Small-Business
  • 39% Mid-Market
InMoment Experience Improvement (XI) Platform Pros and Cons
How are these determined?Information
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Pros
Customer Feedback
5
Feedback Management
5
Helpful
5
Data Management
3
Ease of Use
3
Cons
Filtering Issues
3
AI Limitations
2
Difficult Reporting
2
Expensive
2
Limitations
2
InMoment Experience Improvement (XI) Platform features and usability ratings that predict user satisfaction
0.0
No information available
0.0
No information available
0.0
No information available
9.0
Quality of Support
Average: 8.3
Seller Details
Seller
InMoment
Year Founded
2002
HQ Location
Salt Lake City, UT
Twitter
@WeAreInMoment
1,945 Twitter followers
LinkedIn® Page
www.linkedin.com
745 employees on LinkedIn®
Phone
905-542-9001
Entry Level Price:Free
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    Tune AI is the leading Enterprise GenAI stack for securely fine-tuning models & deploying LLM powered apps. Our offerings include: Tune Chat: An AI chat app with 350,000+ users and powerful model

    Users
    No information available
    Industries
    • Computer Software
    • Information Technology and Services
    Market Segment
    • 75% Small-Business
    • 19% Mid-Market
  • Pros and Cons
    Expand/Collapse Pros and Cons
  • Tune AI Pros and Cons
    How are these determined?Information
    Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
    Pros
    Ease of Use
    96
    Features
    77
    Useful
    72
    Helpful
    58
    User Interface
    51
    Cons
    Limitations
    29
    AI Limitations
    28
    Usage Limitations
    25
    Missing Features
    23
    Technical Issues
    23
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • Tune AI features and usability ratings that predict user satisfaction
    9.2
    Summarization
    Average: 8.9
    10.0
    Language Detection
    Average: 8.8
    10.0
    Part of Speech Tagging
    Average: 8.7
    8.3
    Quality of Support
    Average: 8.3
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Year Founded
    2018
    HQ Location
    San Francisco, US
    Twitter
    @NimbleBoxAI
    474 Twitter followers
    LinkedIn® Page
    in.linkedin.com
    37 employees on LinkedIn®
Product Description
How are these determined?Information
This description is provided by the seller.

Tune AI is the leading Enterprise GenAI stack for securely fine-tuning models & deploying LLM powered apps. Our offerings include: Tune Chat: An AI chat app with 350,000+ users and powerful model

Users
No information available
Industries
  • Computer Software
  • Information Technology and Services
Market Segment
  • 75% Small-Business
  • 19% Mid-Market
Tune AI Pros and Cons
How are these determined?Information
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Pros
Ease of Use
96
Features
77
Useful
72
Helpful
58
User Interface
51
Cons
Limitations
29
AI Limitations
28
Usage Limitations
25
Missing Features
23
Technical Issues
23
Tune AI features and usability ratings that predict user satisfaction
9.2
Summarization
Average: 8.9
10.0
Language Detection
Average: 8.8
10.0
Part of Speech Tagging
Average: 8.7
8.3
Quality of Support
Average: 8.3
Seller Details
Year Founded
2018
HQ Location
San Francisco, US
Twitter
@NimbleBoxAI
474 Twitter followers
LinkedIn® Page
in.linkedin.com
37 employees on LinkedIn®
(10)4.3 out of 5
5th Easiest To Use in Natural Language Understanding (NLU) software
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  • Overview
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  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    Stanford CoreNLP provides a set of natural language analysis tools that can give the base forms of words, their parts of speech, whether they are names of companies, people, etc., normalize dates, tim

    Users
    No information available
    Industries
    No information available
    Market Segment
    • 60% Small-Business
    • 20% Enterprise
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • Stanford CoreNLP features and usability ratings that predict user satisfaction
    0.0
    No information available
    0.0
    No information available
    0.0
    No information available
    6.7
    Quality of Support
    Average: 8.3
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    HQ Location
    Stanford, CA
    Twitter
    @stanfordnlp
    154,929 Twitter followers
    LinkedIn® Page
    www.linkedin.com
    3,992 employees on LinkedIn®
Product Description
How are these determined?Information
This description is provided by the seller.

Stanford CoreNLP provides a set of natural language analysis tools that can give the base forms of words, their parts of speech, whether they are names of companies, people, etc., normalize dates, tim

Users
No information available
Industries
No information available
Market Segment
  • 60% Small-Business
  • 20% Enterprise
Stanford CoreNLP features and usability ratings that predict user satisfaction
0.0
No information available
0.0
No information available
0.0
No information available
6.7
Quality of Support
Average: 8.3
Seller Details
HQ Location
Stanford, CA
Twitter
@stanfordnlp
154,929 Twitter followers
LinkedIn® Page
www.linkedin.com
3,992 employees on LinkedIn®
  • Overview
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  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    NLTK is a platform for building Python programs to work with human language data that provides interfaces to corpora and lexical resources such as WordNet, along with a suite of text processing librar

    Users
    • Data Scientist
    • Software Engineer
    Industries
    • Information Technology and Services
    • Computer Software
    Market Segment
    • 52% Small-Business
    • 29% Enterprise
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • NLTK features and usability ratings that predict user satisfaction
    7.4
    Summarization
    Average: 8.9
    7.0
    Language Detection
    Average: 8.8
    7.4
    Part of Speech Tagging
    Average: 8.7
    8.2
    Quality of Support
    Average: 8.3
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    HQ Location
    N/A
    Twitter
    @NLTK_org
    2,463 Twitter followers
Product Description
How are these determined?Information
This description is provided by the seller.

NLTK is a platform for building Python programs to work with human language data that provides interfaces to corpora and lexical resources such as WordNet, along with a suite of text processing librar

Users
  • Data Scientist
  • Software Engineer
Industries
  • Information Technology and Services
  • Computer Software
Market Segment
  • 52% Small-Business
  • 29% Enterprise
NLTK features and usability ratings that predict user satisfaction
7.4
Summarization
Average: 8.9
7.0
Language Detection
Average: 8.8
7.4
Part of Speech Tagging
Average: 8.7
8.2
Quality of Support
Average: 8.3
Seller Details
HQ Location
N/A
Twitter
@NLTK_org
2,463 Twitter followers
  • Overview
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  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    MITIE: MIT Information Extraction is a tool that include performing named entity extraction and binary relation detection for training custom extractors and relation detectors.

    Users
    No information available
    Industries
    No information available
    Market Segment
    • 42% Enterprise
    • 33% Small-Business
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • MITIE: MIT Information Extraction features and usability ratings that predict user satisfaction
    8.3
    Summarization
    Average: 8.9
    8.3
    Language Detection
    Average: 8.8
    8.9
    Part of Speech Tagging
    Average: 8.7
    9.4
    Quality of Support
    Average: 8.3
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Seller
    MITIE
    Year Founded
    1987
    HQ Location
    London, UK
    LinkedIn® Page
    www.linkedin.com
    16,660 employees on LinkedIn®
    Ownership
    LON: MTO
Product Description
How are these determined?Information
This description is provided by the seller.

MITIE: MIT Information Extraction is a tool that include performing named entity extraction and binary relation detection for training custom extractors and relation detectors.

Users
No information available
Industries
No information available
Market Segment
  • 42% Enterprise
  • 33% Small-Business
MITIE: MIT Information Extraction features and usability ratings that predict user satisfaction
8.3
Summarization
Average: 8.9
8.3
Language Detection
Average: 8.8
8.9
Part of Speech Tagging
Average: 8.7
9.4
Quality of Support
Average: 8.3
Seller Details
Seller
MITIE
Year Founded
1987
HQ Location
London, UK
LinkedIn® Page
www.linkedin.com
16,660 employees on LinkedIn®
Ownership
LON: MTO
  • Overview
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  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    Gensim is a Python library that analyze plain-text documents for semantic structure and retrieve semantically similar document.

    Users
    No information available
    Industries
    No information available
    Market Segment
    • 53% Small-Business
    • 27% Enterprise
  • Pros and Cons
    Expand/Collapse Pros and Cons
  • Gensim Pros and Cons
    How are these determined?Information
    Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
    Pros
    This product has not yet received any positive sentiments.
    Cons
    Expensive
    1
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • Gensim features and usability ratings that predict user satisfaction
    7.6
    Summarization
    Average: 8.9
    7.6
    Language Detection
    Average: 8.8
    8.0
    Part of Speech Tagging
    Average: 8.7
    9.1
    Quality of Support
    Average: 8.3
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    HQ Location
    N/A
    LinkedIn® Page
    www.linkedin.com
    1 employees on LinkedIn®
Product Description
How are these determined?Information
This description is provided by the seller.

Gensim is a Python library that analyze plain-text documents for semantic structure and retrieve semantically similar document.

Users
No information available
Industries
No information available
Market Segment
  • 53% Small-Business
  • 27% Enterprise
Gensim Pros and Cons
How are these determined?Information
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Pros
This product has not yet received any positive sentiments.
Cons
Expensive
1
Gensim features and usability ratings that predict user satisfaction
7.6
Summarization
Average: 8.9
7.6
Language Detection
Average: 8.8
8.0
Part of Speech Tagging
Average: 8.7
9.1
Quality of Support
Average: 8.3
Seller Details
HQ Location
N/A
LinkedIn® Page
www.linkedin.com
1 employees on LinkedIn®
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    The Industry’s Only Low‑Code, Integrated, End‑to‑End Intelligent Automation Solution Tungsten TotalAgility is a powerful all-in-one solution that combines document and process intelligence using the

    Users
    No information available
    Industries
    • Banking
    • Information Technology and Services
    Market Segment
    • 53% Enterprise
    • 31% Mid-Market
  • Pros and Cons
    Expand/Collapse Pros and Cons
  • Tungsten TotalAgility Pros and Cons
    How are these determined?Information
    Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
    Pros
    Capabilities
    5
    Ease of Use
    5
    OCR Technology
    5
    Data Extraction
    4
    Low Code
    4
    Cons
    Bugs
    3
    Complexity
    3
    Performance Issues
    3
    Support Issues
    3
    Customization Difficulty
    2
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • Tungsten TotalAgility features and usability ratings that predict user satisfaction
    10.0
    Summarization
    Average: 8.9
    10.0
    Language Detection
    Average: 8.8
    10.0
    Part of Speech Tagging
    Average: 8.7
    8.3
    Quality of Support
    Average: 8.3
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Year Founded
    1985
    HQ Location
    Irvine, California