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Best Data Labeling Software - Page 2

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Researched and written by Sohan Pal

Data labeling software are an artificial intelligence tools that supervises data management, training data, model versioning, data sourcing, data annotation, quality control, and model production for data science and machine learning teams. These tools source, manage, label, train, and classify unstructured data such as texts, videos, images, audio, or PDF into labeled datasets to create efficient training data pipelines.

Data labeling, also known as data annotation tools or data tagging, is a building block for an AI development lifecycle for businesses. Businesses deploy data labeling software for industry-based applications like ML model generation, fine-tuning large language models (LLM), evaluating LLMs, computer vision, image segmentation, API calls, object detection, and tracking, named entity recognition, OCR, and text recognition. These AI models reduce the classification challenges for data science and machine learning teams and improve AI data management workflows to build efficient machine learning products.

Businesses use data labeling tools to label text data, audio files, images, and videos and gather real-time feedback from customers, stakeholders, and decision-makers to upgrade products. These tools are also used for sentimental analysis, question answering, speech recognition, and content generation. Data labeling tools can be integrated with generative AI software, project management software, MLOPs platforms, data science and machine learning platforms, LLM software, and active learning tools to label data, pre-train models, assure quality control, and operationalize ML production.

Additionally, these products provide security, provisioning, and governing capabilities to ensure only those authorized to make version changes or deployment adjustments can do so. These data labeling tools can differ in what part of the machine learning journey or workflow they focus on, including explainability, model testing, model validation, feature engineering, model risk, model selection, model monitoring, and experiment tracking. The ultimate goal of a data labeling platform is to build agile, precise, and cost-effective data training pipelines to enhance model response accuracy.

To qualify for inclusion in the Data Labeling category, a product must:

Integrate a managed workforce and/or data labeling service
Ensure labels are accurate and consistent
Give the user the ability to view analytics that monitor the accuracy and/or speed of labeling
Allow the annotated data to be integrated into data science and machine learning platforms to build machine learning models
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Best Data Labeling Software At A Glance

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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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87 Listings in Data Labeling Available
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    BasicAI Data Annotation Platform (https://www.basic.ai/basicai-cloud-data-annotation-platform) is an All-in-One Smart Data Annotation Platform with strong multimodal feature and AI-powered annotation

    Users
    No information available
    Industries
    • Information Technology and Services
    • Computer Software
    Market Segment
    • 44% Small-Business
    • 31% Mid-Market
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • BasicAI Data Annotation Platform features and usability ratings that predict user satisfaction
    8.9
    Labeler Quality
    Average: 8.9
    8.8
    Object Detection
    Average: 8.9
    8.8
    Data Types
    Average: 8.8
    8.5
    Ease of Use
    Average: 8.8
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Seller
    BasicAI
    Year Founded
    2019
    HQ Location
    Irvine, CA
    Twitter
    @BasicAIteam
    93 Twitter followers
    LinkedIn® Page
    www.linkedin.com
    15 employees on LinkedIn®
Product Description
How are these determined?Information
This description is provided by the seller.

BasicAI Data Annotation Platform (https://www.basic.ai/basicai-cloud-data-annotation-platform) is an All-in-One Smart Data Annotation Platform with strong multimodal feature and AI-powered annotation

Users
No information available
Industries
  • Information Technology and Services
  • Computer Software
Market Segment
  • 44% Small-Business
  • 31% Mid-Market
BasicAI Data Annotation Platform features and usability ratings that predict user satisfaction
8.9
Labeler Quality
Average: 8.9
8.8
Object Detection
Average: 8.9
8.8
Data Types
Average: 8.8
8.5
Ease of Use
Average: 8.8
Seller Details
Seller
BasicAI
Year Founded
2019
HQ Location
Irvine, CA
Twitter
@BasicAIteam
93 Twitter followers
LinkedIn® Page
www.linkedin.com
15 employees on LinkedIn®
(13)4.5 out of 5
View top Consulting Services for Alegion
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  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    Alegion's managed service accelerates enterprise AI initiatives by validating, labeling, and annotating training data.

    Users
    No information available
    Industries
    • Computer Software
    Market Segment
    • 38% Small-Business
    • 31% Enterprise
  • Pros and Cons
    Expand/Collapse Pros and Cons
  • Alegion 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
    Features
    4
    Data Labelling
    3
    Data Management
    3
    Annotation Efficiency
    2
    Customer Support
    2
    Cons
    Expensive
    3
    Complexity
    2
    Limited Customization
    2
    Difficult Learning
    1
    Lack of Features
    1
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • Alegion features and usability ratings that predict user satisfaction
    8.8
    Labeler Quality
    Average: 8.9
    9.1
    Object Detection
    Average: 8.9
    9.6
    Data Types
    Average: 8.8
    8.8
    Ease of Use
    Average: 8.8
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Seller
    Alegion
    Year Founded
    2012
    HQ Location
    Austin, US
    Twitter
    @Alegion
    1,723 Twitter followers
    LinkedIn® Page
    www.linkedin.com
    43 employees on LinkedIn®
Product Description
How are these determined?Information
This description is provided by the seller.

Alegion's managed service accelerates enterprise AI initiatives by validating, labeling, and annotating training data.

Users
No information available
Industries
  • Computer Software
Market Segment
  • 38% Small-Business
  • 31% Enterprise
Alegion 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
Features
4
Data Labelling
3
Data Management
3
Annotation Efficiency
2
Customer Support
2
Cons
Expensive
3
Complexity
2
Limited Customization
2
Difficult Learning
1
Lack of Features
1
Alegion features and usability ratings that predict user satisfaction
8.8
Labeler Quality
Average: 8.9
9.1
Object Detection
Average: 8.9
9.6
Data Types
Average: 8.8
8.8
Ease of Use
Average: 8.8
Seller Details
Seller
Alegion
Year Founded
2012
HQ Location
Austin, US
Twitter
@Alegion
1,723 Twitter followers
LinkedIn® Page
www.linkedin.com
43 employees on LinkedIn®

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  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    Playment’s GT Studio is a no-code, self-serve data labeling platform that is heuristically designed to help ML teams create diverse, high-quality ground truth datasets at an efficient cost, scale, and

    Users
    No information available
    Industries
    • Computer Software
    Market Segment
    • 36% Enterprise
    • 36% Small-Business
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • Playment features and usability ratings that predict user satisfaction
    8.9
    Labeler Quality
    Average: 8.9
    8.9
    Object Detection
    Average: 8.9
    10.0
    Data Types
    Average: 8.8
    9.7
    Ease of Use
    Average: 8.8
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Seller
    Playment
    Year Founded
    2005
    HQ Location
    Las Vegas, US
    LinkedIn® Page
    www.linkedin.com
    5,062 employees on LinkedIn®
Product Description
How are these determined?Information
This description is provided by the seller.

Playment’s GT Studio is a no-code, self-serve data labeling platform that is heuristically designed to help ML teams create diverse, high-quality ground truth datasets at an efficient cost, scale, and

Users
No information available
Industries
  • Computer Software
Market Segment
  • 36% Enterprise
  • 36% Small-Business
Playment features and usability ratings that predict user satisfaction
8.9
Labeler Quality
Average: 8.9
8.9
Object Detection
Average: 8.9
10.0
Data Types
Average: 8.8
9.7
Ease of Use
Average: 8.8
Seller Details
Seller
Playment
Year Founded
2005
HQ Location
Las Vegas, US
LinkedIn® Page
www.linkedin.com
5,062 employees on LinkedIn®
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    Labellerr is a computer vision workflow automation platform. It helps ML teams to manage their AI development lifecycle much more efficiently. It helps teams to collaboratively work on data labeling

    Users
    No information available
    Industries
    • Information Technology and Services
    Market Segment
    • 57% Small-Business
    • 38% Mid-Market
  • Pros and Cons
    Expand/Collapse Pros and Cons
  • Labellerr 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
    Annotation Efficiency
    3
    Customer Support
    3
    Ease of Use
    3
    Analytics
    2
    Data Labeling
    2
    Cons
    Difficult Setup
    1
    Lacking Features
    1
    Lack of Features
    1
    Limited Customization
    1
    Missing Features
    1
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • Labellerr features and usability ratings that predict user satisfaction
    9.9
    Labeler Quality
    Average: 8.9
    9.7
    Object Detection
    Average: 8.9
    9.9
    Data Types
    Average: 8.8
    9.6
    Ease of Use
    Average: 8.8
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Year Founded
    2017
    HQ Location
    Wilmington, Delaware
    Twitter
    @Labellerr1
    105 Twitter followers
    LinkedIn® Page
    www.linkedin.com
    2 employees on LinkedIn®
Product Description
How are these determined?Information
This description is provided by the seller.

Labellerr is a computer vision workflow automation platform. It helps ML teams to manage their AI development lifecycle much more efficiently. It helps teams to collaboratively work on data labeling

Users
No information available
Industries
  • Information Technology and Services
Market Segment
  • 57% Small-Business
  • 38% Mid-Market
Labellerr 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
Annotation Efficiency
3
Customer Support
3
Ease of Use
3
Analytics
2
Data Labeling
2
Cons
Difficult Setup
1
Lacking Features
1
Lack of Features
1
Limited Customization
1
Missing Features
1
Labellerr features and usability ratings that predict user satisfaction
9.9
Labeler Quality
Average: 8.9
9.7
Object Detection
Average: 8.9
9.9
Data Types
Average: 8.8
9.6
Ease of Use
Average: 8.8
Seller Details
Year Founded
2017
HQ Location
Wilmington, Delaware
Twitter
@Labellerr1
105 Twitter followers
LinkedIn® Page
www.linkedin.com
2 employees on LinkedIn®
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    Shaip Data is a modern platform designed to gather high-quality, ethical data for training AI models. It has three main parts: Shaip Manage, Shaip Work, and Shaip Intelligence. The platform makes wor

    Users
    No information available
    Industries
    • Computer Software
    Market Segment
    • 41% Enterprise
    • 36% Small-Business
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • Shaip Cloud features and usability ratings that predict user satisfaction
    8.3
    Labeler Quality
    Average: 8.9
    8.5
    Object Detection
    Average: 8.9
    8.7
    Data Types
    Average: 8.8
    8.3
    Ease of Use
    Average: 8.8
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Seller
    Shaip
    Year Founded
    2018
    HQ Location
    Louisville, Kentucky
    Twitter
    @weareShaip
    237 Twitter followers
    LinkedIn® Page
    www.linkedin.com
    331 employees on LinkedIn®
Product Description
How are these determined?Information
This description is provided by the seller.

Shaip Data is a modern platform designed to gather high-quality, ethical data for training AI models. It has three main parts: Shaip Manage, Shaip Work, and Shaip Intelligence. The platform makes wor

Users
No information available
Industries
  • Computer Software
Market Segment
  • 41% Enterprise
  • 36% Small-Business
Shaip Cloud features and usability ratings that predict user satisfaction
8.3
Labeler Quality
Average: 8.9
8.5
Object Detection
Average: 8.9
8.7
Data Types
Average: 8.8
8.3
Ease of Use
Average: 8.8
Seller Details
Seller
Shaip
Year Founded
2018
HQ Location
Louisville, Kentucky
Twitter
@weareShaip
237 Twitter followers
LinkedIn® Page
www.linkedin.com
331 employees on LinkedIn®
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    Kili Technology is a comprehensive labeling tool where you can label your training data fast, find and fix issues in your dataset, and simplify your labeling operations. Kili Technology dramatically a

    Users
    No information available
    Industries
    • Information Technology and Services
    • Computer Software
    Market Segment
    • 40% Mid-Market
    • 38% Small-Business
  • Pros and Cons
    Expand/Collapse Pros and Cons
  • Kili 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
    API Quality
    2
    API Usability
    2
    Collaboration
    2
    Data Labeling
    2
    Data Management
    2
    Cons
    Annotation Issues
    1
    Complex Implementation
    1
    Inefficient Labeling
    1
    Lacking Features
    1
    Lack of Features
    1
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • Kili features and usability ratings that predict user satisfaction
    9.2
    Labeler Quality
    Average: 8.9
    9.2
    Object Detection
    Average: 8.9
    9.2
    Data Types
    Average: 8.8
    8.8
    Ease of Use
    Average: 8.8
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Year Founded
    2018
    HQ Location
    Paris, FR
    Twitter
    @Kili_Technology
    444 Twitter followers
    LinkedIn® Page
    www.linkedin.com
    40 employees on LinkedIn®
Product Description
How are these determined?Information
This description is provided by the seller.

Kili Technology is a comprehensive labeling tool where you can label your training data fast, find and fix issues in your dataset, and simplify your labeling operations. Kili Technology dramatically a

Users
No information available
Industries
  • Information Technology and Services
  • Computer Software
Market Segment
  • 40% Mid-Market
  • 38% Small-Business
Kili 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
API Quality
2
API Usability
2
Collaboration
2
Data Labeling
2
Data Management
2
Cons
Annotation Issues
1
Complex Implementation
1
Inefficient Labeling
1
Lacking Features
1
Lack of Features
1
Kili features and usability ratings that predict user satisfaction
9.2
Labeler Quality
Average: 8.9
9.2
Object Detection
Average: 8.9
9.2
Data Types
Average: 8.8
8.8
Ease of Use
Average: 8.8
Seller Details
Year Founded
2018
HQ Location
Paris, FR
Twitter
@Kili_Technology
444 Twitter followers
LinkedIn® Page
www.linkedin.com
40 employees on LinkedIn®
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    Founded in 2013, Hive is a pioneering AI company specialized in computer vision and deep learning. Hive is focused on powering innovators across industries with practical AI solutions and data labelin

    Users
    No information available
    Industries
    No information available
    Market Segment
    • 50% Enterprise
    • 40% Small-Business
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • Hive Data features and usability ratings that predict user satisfaction
    7.5
    Labeler Quality
    Average: 8.9
    10.0
    Object Detection
    Average: 8.9
    6.7
    Data Types
    Average: 8.8
    8.9
    Ease of Use
    Average: 8.8
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Seller
    Hive.ai
    Year Founded
    2013
    HQ Location
    San Francisco, California
    Twitter
    @hive_ai
    1,305 Twitter followers
    LinkedIn® Page
    www.linkedin.com
    500 employees on LinkedIn®
Product Description
How are these determined?Information
This description is provided by the seller.

Founded in 2013, Hive is a pioneering AI company specialized in computer vision and deep learning. Hive is focused on powering innovators across industries with practical AI solutions and data labelin

Users
No information available
Industries
No information available
Market Segment
  • 50% Enterprise
  • 40% Small-Business
Hive Data features and usability ratings that predict user satisfaction
7.5
Labeler Quality
Average: 8.9
10.0
Object Detection
Average: 8.9
6.7
Data Types
Average: 8.8
8.9
Ease of Use
Average: 8.8
Seller Details
Seller
Hive.ai
Year Founded
2013
HQ Location
San Francisco, California
Twitter
@hive_ai
1,305 Twitter followers
LinkedIn® Page
www.linkedin.com
500 employees on LinkedIn®
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    Multi-sensor labeling platform for robotics and autonomous driving. Segments.ai is a fast and accurate data labeling platform for multi-sensor data annotation. You can obtain segmentation labels, vec

    Users
    No information available
    Industries
    • Research
    Market Segment
    • 95% Small-Business
    • 5% Mid-Market
  • Pros and Cons
    Expand/Collapse Pros and Cons
  • Segments.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
    Data Labeling
    3
    Efficiency
    3
    Features
    3
    Image Segmentation
    3
    Customer Support
    2
    Cons
    Difficult Learning
    3
    Learning Curve
    3
    Annotation Issues
    1
    Lack of Features
    1
    Lack of Guidance
    1
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • Segments.ai features and usability ratings that predict user satisfaction
    8.9
    Labeler Quality
    Average: 8.9
    8.3
    Object Detection
    Average: 8.9
    8.0
    Data Types
    Average: 8.8
    8.6
    Ease of Use
    Average: 8.8
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Year Founded
    2020
    HQ Location
    Leuven, Vlaams-Brabant, Belgium
    Twitter
    @SegmentsAI
    483 Twitter followers
    LinkedIn® Page
    www.linkedin.com
    11 employees on LinkedIn®
Product Description
How are these determined?Information
This description is provided by the seller.

Multi-sensor labeling platform for robotics and autonomous driving. Segments.ai is a fast and accurate data labeling platform for multi-sensor data annotation. You can obtain segmentation labels, vec

Users
No information available
Industries
  • Research
Market Segment
  • 95% Small-Business
  • 5% Mid-Market
Segments.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
Data Labeling
3
Efficiency
3
Features
3
Image Segmentation
3
Customer Support
2
Cons
Difficult Learning
3
Learning Curve
3
Annotation Issues
1
Lack of Features
1
Lack of Guidance
1
Segments.ai features and usability ratings that predict user satisfaction
8.9
Labeler Quality
Average: 8.9
8.3
Object Detection
Average: 8.9
8.0
Data Types
Average: 8.8
8.6
Ease of Use
Average: 8.8
Seller Details
Year Founded
2020
HQ Location
Leuven, Vlaams-Brabant, Belgium
Twitter
@SegmentsAI
483 Twitter followers
LinkedIn® Page
www.linkedin.com
11 employees on LinkedIn®
(29)4.5 out of 5
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  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    Datasaur offers the most intuitive interface for all your Natural Language Processing related tasks.

    Users
    No information available
    Industries
    • Computer Software
    Market Segment
    • 52% Mid-Market
    • 41% Small-Business
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • Datasaur features and usability ratings that predict user satisfaction
    8.9
    Labeler Quality
    Average: 8.9
    8.2
    Object Detection
    Average: 8.9
    8.3
    Data Types
    Average: 8.8
    9.3
    Ease of Use
    Average: 8.8
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Seller
    Datasaur
    Year Founded
    2019
    HQ Location
    San Francisco Bay Area, California
    Twitter
    @datasaurai
    263 Twitter followers
    LinkedIn® Page
    www.linkedin.com
    68 employees on LinkedIn®
Product Description
How are these determined?Information
This description is provided by the seller.

Datasaur offers the most intuitive interface for all your Natural Language Processing related tasks.

Users
No information available
Industries
  • Computer Software
Market Segment
  • 52% Mid-Market
  • 41% Small-Business
Datasaur features and usability ratings that predict user satisfaction
8.9
Labeler Quality
Average: 8.9
8.2
Object Detection
Average: 8.9
8.3
Data Types
Average: 8.8
9.3
Ease of Use
Average: 8.8
Seller Details
Seller
Datasaur
Year Founded
2019
HQ Location
San Francisco Bay Area, California
Twitter
@datasaurai
263 Twitter followers
LinkedIn® Page
www.linkedin.com
68 employees on LinkedIn®
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    Supercharge your AI with human expertise. SUPA is here to help you streamline your data at any stage: collection, curation, annotation, model validation and human feedback. SUPA is trusted by AI tea

    Users
    No information available
    Industries
    No information available
    Market Segment
    • 45% Small-Business
    • 45% Mid-Market
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • SUPA features and usability ratings that predict user satisfaction
    8.8
    Labeler Quality
    Average: 8.9
    9.7
    Object Detection
    Average: 8.9
    9.2
    Data Types
    Average: 8.8
    9.3
    Ease of Use
    Average: 8.8
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Seller
    SUPA
    Year Founded
    2014
    HQ Location
    Damansara Heights, MY
    Twitter
    @SUPABOLT
    13 Twitter followers
    LinkedIn® Page
    www.linkedin.com
    67 employees on LinkedIn®
Product Description
How are these determined?Information
This description is provided by the seller.

Supercharge your AI with human expertise. SUPA is here to help you streamline your data at any stage: collection, curation, annotation, model validation and human feedback. SUPA is trusted by AI tea

Users
No information available
Industries
No information available
Market Segment
  • 45% Small-Business
  • 45% Mid-Market
SUPA features and usability ratings that predict user satisfaction
8.8
Labeler Quality
Average: 8.9
9.7
Object Detection
Average: 8.9
9.2
Data Types
Average: 8.8
9.3
Ease of Use
Average: 8.8
Seller Details
Seller
SUPA
Year Founded
2014
HQ Location
Damansara Heights, MY
Twitter
@SUPABOLT
13 Twitter followers
LinkedIn® Page
www.linkedin.com
67 employees on LinkedIn®
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    UBIAI makes easy-to-use NLP tools to help companies analyze and extract actionable insights from their unstructured data.

    Users
    No information available
    Industries
    No information available
    Market Segment
    • 47% Small-Business
    • 35% Mid-Market
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • UBIAI Text Annotation Tool features and usability ratings that predict user satisfaction
    9.0
    Labeler Quality
    Average: 8.9
    8.8
    Object Detection
    Average: 8.9
    9.0
    Data Types
    Average: 8.8
    9.2
    Ease of Use
    Average: 8.8
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Seller
    UBIAI
    Year Founded
    2020
    HQ Location
    Carlsbad, US
    Twitter
    @UBIAI5
    128 Twitter followers
    LinkedIn® Page
    www.linkedin.com
    14 employees on LinkedIn®
Product Description
How are these determined?Information
This description is provided by the seller.

UBIAI makes easy-to-use NLP tools to help companies analyze and extract actionable insights from their unstructured data.

Users
No information available
Industries
No information available
Market Segment
  • 47% Small-Business
  • 35% Mid-Market
UBIAI Text Annotation Tool features and usability ratings that predict user satisfaction
9.0
Labeler Quality
Average: 8.9
8.8
Object Detection
Average: 8.9
9.0
Data Types
Average: 8.8
9.2
Ease of Use
Average: 8.8
Seller Details
Seller
UBIAI
Year Founded
2020
HQ Location
Carlsbad, US
Twitter
@UBIAI5
128 Twitter followers
LinkedIn® Page
www.linkedin.com
14 employees on LinkedIn®
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    This solution automatically identifies and trains the best performing deep learning model for text classification.

    Users
    No information available
    Industries
    No information available
    Market Segment
    • 46% Mid-Market
    • 38% Enterprise
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • Text Classifier with auto Deep Learning features and usability ratings that predict user satisfaction
    9.7
    Labeler Quality
    Average: 8.9
    9.7
    Object Detection
    Average: 8.9
    9.7
    Data Types
    Average: 8.8
    9.2
    Ease of Use
    Average: 8.8
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Seller
    Mphasis
    Year Founded
    2007
    HQ Location
    Reston, VA
    Twitter
    @Stelligent
    1,120 Twitter followers
    LinkedIn® Page
    www.linkedin.com
    19 employees on LinkedIn®
Product Description
How are these determined?Information
This description is provided by the seller.

This solution automatically identifies and trains the best performing deep learning model for text classification.

Users
No information available
Industries
No information available
Market Segment
  • 46% Mid-Market
  • 38% Enterprise
Text Classifier with auto Deep Learning features and usability ratings that predict user satisfaction
9.7
Labeler Quality
Average: 8.9
9.7
Object Detection
Average: 8.9
9.7
Data Types
Average: 8.8
9.2
Ease of Use
Average: 8.8
Seller Details
Seller
Mphasis
Year Founded
2007
HQ Location
Reston, VA
Twitter
@Stelligent
1,120 Twitter followers
LinkedIn® Page
www.linkedin.com
19 employees on LinkedIn®
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    Build better AI data faster! LinkedAI is a complete solution for taking control of your training data, with fast labeling tools, human workforce, data management, and automation features. An AI model

    Users
    No information available
    Industries
    • Computer Software
    Market Segment
    • 43% Mid-Market
    • 30% Small-Business
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • LinkedAI features and usability ratings that predict user satisfaction
    9.4
    Labeler Quality
    Average: 8.9
    8.5
    Object Detection
    Average: 8.9
    8.9
    Data Types
    Average: 8.8
    8.7
    Ease of Use
    Average: 8.8
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Seller
    LinkedAI
    Year Founded
    2018
    HQ Location
    Sunnyvale, CA
    Twitter
    @LinkedAI
    111 Twitter followers
    LinkedIn® Page
    www.linkedin.com
    13 employees on LinkedIn®
Product Description
How are these determined?Information
This description is provided by the seller.

Build better AI data faster! LinkedAI is a complete solution for taking control of your training data, with fast labeling tools, human workforce, data management, and automation features. An AI model

Users
No information available
Industries
  • Computer Software
Market Segment
  • 43% Mid-Market
  • 30% Small-Business
LinkedAI features and usability ratings that predict user satisfaction
9.4
Labeler Quality
Average: 8.9
8.5
Object Detection
Average: 8.9
8.9
Data Types
Average: 8.8
8.7
Ease of Use
Average: 8.8
Seller Details
Seller
LinkedAI
Year Founded
2018
HQ Location
Sunnyvale, CA
Twitter
@LinkedAI
111 Twitter followers
LinkedIn® Page
www.linkedin.com
13 employees on LinkedIn®
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    Innotescus is a collaborative video and image annotation platform built to streamline Computer Vision development processes via seamless data handling, smart annotation tools, and intuitive collaborat

    Users
    No information available
    Industries
    No information available
    Market Segment
    • 70% Small-Business
    • 10% Enterprise
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • Innotescus Video and Image Annotation Platform features and usability ratings that predict user satisfaction
    8.3
    Labeler Quality
    Average: 8.9
    10.0
    Object Detection
    Average: 8.9
    10.0
    Data Types
    Average: 8.8
    9.0
    Ease of Use
    Average: 8.8
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Year Founded
    2018
    HQ Location
    Pittsburgh
    Twitter
    @innotescus
    128 Twitter followers
    LinkedIn® Page
    www.linkedin.com
    1 employees on LinkedIn®
Product Description
How are these determined?Information
This description is provided by the seller.

Innotescus is a collaborative video and image annotation platform built to streamline Computer Vision development processes via seamless data handling, smart annotation tools, and intuitive collaborat

Users
No information available
Industries
No information available
Market Segment
  • 70% Small-Business
  • 10% Enterprise
Innotescus Video and Image Annotation Platform features and usability ratings that predict user satisfaction
8.3
Labeler Quality
Average: 8.9
10.0
Object Detection
Average: 8.9
10.0
Data Types
Average: 8.8
9.0
Ease of Use
Average: 8.8
Seller Details
Year Founded
2018
HQ Location
Pittsburgh
Twitter
@innotescus
128 Twitter followers
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.

    Super.AI Intelligent Document Processing (IDP) extracts data from any document, ensuring seamless automation, reduced costs, and smarter decisions. 91-99%+ Accuracy $100M+ in Costs Saved 1M+Hours

    Users
    No information available
    Industries
    No information available
    Market Segment
    • 50% Mid-Market
    • 42% Small-Business
  • Pros and Cons
    Expand/Collapse Pros and Cons
  • super.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
    Helpful
    1
    Cons
    This product has not yet received any negative sentiments.
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • super.AI features and usability ratings that predict user satisfaction
    8.3
    Labeler Quality
    Average: 8.9
    9.2
    Object Detection
    Average: 8.9
    9.2
    Data Types
    Average: 8.8
    8.1
    Ease of Use
    Average: 8.8
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Seller
    super.AI
    Year Founded
    2018
    HQ Location
    Bellevue, Washington
    Twitter
    @mysuperai
    431 Twitter followers
    LinkedIn® Page
    www.linkedin.com
    41 employees on LinkedIn®
Product Description
How are these determined?Information
This description is provided by the seller.

Super.AI Intelligent Document Processing (IDP) extracts data from any document, ensuring seamless automation, reduced costs, and smarter decisions. 91-99%+ Accuracy $100M+ in Costs Saved 1M+Hours

Users
No information available
Industries
No information available
Market Segment
  • 50% Mid-Market
  • 42% Small-Business
super.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
Helpful
1
Cons
This product has not yet received any negative sentiments.
super.AI features and usability ratings that predict user satisfaction
8.3
Labeler Quality
Average: 8.9
9.2
Object Detection
Average: 8.9
9.2
Data Types
Average: 8.8
8.1
Ease of Use
Average: 8.8
Seller Details
Seller
super.AI
Year Founded
2018
HQ Location
Bellevue, Washington
Twitter
@mysuperai
431 Twitter followers
LinkedIn® Page
www.linkedin.com
41 employees on LinkedIn®