Compare Labellerr and V7 
At a Glance
Market Segments
Small-Business (57.1% of reviews)
Small-Business (56.9% of reviews)
Entry-Level Pricing
Contact Us Per Month
Free
Labellerr
Star Rating
(21)4.8 out of 5
Market Segments
Small-Business (57.1% of reviews)
Entry-Level Pricing
Contact Us Per Month
Browse all 3 pricing plansV7
Star Rating
(53)4.8 out of 5
Market Segments
Small-Business (56.9% of reviews)
Entry-Level Pricing
Free
Browse all 4 pricing plansSummary
AI Generated Summary
AI-generated. Powered by real user reviews.
- Users report that Labellerr excels in Labeler Quality with a score of 9.9, while V7's score of 9.4 indicates it may not match the same level of precision in labeling tasks. Reviewers mention that Labellerr's labeling tools are particularly effective for complex datasets.
- Reviewers mention that V7 offers a Free Entry Level Price, making it more accessible for small businesses looking to start without a financial commitment, whereas Labellerr requires potential users to contact for pricing, which can be a barrier for some.
- Users on G2 highlight Labellerr's superior Human-in-the-Loop feature with a score of 9.3 compared to V7's 9.4, indicating that Labellerr provides a more robust framework for integrating human feedback into the labeling process, enhancing overall data quality.
- G2 users report that V7 shines in Automation features, particularly with its Machine Learning Pre-Labeling scoring 9.3, which helps streamline workflows. In contrast, Labellerr's score of 9.6 suggests it may not be as efficient in automating repetitive tasks.
- Reviewers mention that Labellerr's Model Training capabilities are top-notch, scoring a perfect 10.0, while V7's score of 9.0 indicates it may not provide the same level of support for users looking to develop and optimize their models effectively.
- Users say that V7's Collaboration features, scoring a perfect 10.0, are highly praised for facilitating teamwork, while Labellerr's score of 9.3 suggests it may not offer the same level of collaborative tools, which could impact team efficiency.
Pricing
Entry-Level Pricing
Labellerr
Enterprise Plan
Contact Us
Per Month
- Seat Available: Unlimited
- Data Credit: Unlimited
- Datatype support: jpg, png, wav, mp4, pdf, txt, dicom, lidar, nifti
V7
Free Plan
Free
Try out the core functionalities and set up your workflow for free.
- 1 Workspace
- 10 User Licenses
- 3 Integrated Models
Free Trial
Labellerr
Free Trial is available
V7
Free Trial is available
Ratings
Meets Requirements
9.4
18
9.5
37
Ease of Use
9.6
18
9.6
37
Ease of Setup
9.2
8
9.7
16
Ease of Admin
9.0
8
9.4
15
Quality of Support
9.7
18
9.6
35
Has the product been a good partner in doing business?
9.8
8
9.9
14
Product Direction (% positive)
10.0
18
9.6
31
Features by Category
Deployment
Not enough data
Not enough data
Not enough data
9.4
6
Not enough data
9.7
5
Not enough data
9.0
7
Not enough data
9.8
7
Deployment
Not enough data
Not enough data
Not enough data
9.3
5
Not enough data
9.7
6
Not enough data
9.2
6
Not enough data
9.8
7
Management
Not enough data
9.3
5
Not enough data
10.0
6
Not enough data
Not enough data
Not enough data
Not enough data
Operations
Not enough data
9.7
6
Not enough data
Not enough data
Not enough data
10.0
6
Management
Not enough data
10.0
5
Not enough data
9.7
5
Not enough data
9.3
5
Generative AI
Feature Not Available
Feature Not Available
Feature Not Available
Feature Not Available
System
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Model Development
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
10.0
5
Not enough data
10.0
5
Model Development
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Machine/Deep Learning Services
Not enough data
10.0
5
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
10.0
5
Machine/Deep Learning Services
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Deployment
Not enough data
10.0
5
Not enough data
10.0
5
Not enough data
10.0
5
Deployment
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Generative AI
Feature Not Available
Feature Not Available
Feature Not Available
Feature Not Available
Feature Not Available
Feature Not Available
Quality
9.9
12
9.4
20
9.7
12
9.5
23
9.9
13
9.3
20
9.3
14
9.4
21
Automation
9.6
13
9.3
15
9.5
13
9.5
13
Image Annotation
9.6
13
9.4
26
9.7
13
9.6
23
9.7
13
9.1
16
9.9
13
9.1
17
Natural Language Annotation
9.9
12
9.2
12
9.6
13
9.0
8
9.8
11
9.3
9
Speech Annotation
9.9
12
7.6
7
9.6
12
8.1
7
Recognition Type
Not enough data
Not enough data
Not enough data
9.6
8
Not enough data
9.7
5
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
9.3
5
Facial Recognition
Not enough data
10.0
5
Not enough data
Not enough data
Labeling
Not enough data
10.0
8
Not enough data
9.8
8
Not enough data
9.8
8
Deployment
Not enough data
Not enough data
Operating System
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Document Processing
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Platform Additional Functionality
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Data Capture
Not enough data
Not enough data
Not enough data
Not enough data
Data Extraction
Not enough data
Not enough data
Not enough data
Not enough data
Data Validation
Not enough data
Not enough data
Workflow Automation
Not enough data
Not enough data
Not enough data
Not enough data
Document Management
Not enough data
Not enough data
Not enough data
Not enough data
Machine Learning
Not enough data
Not enough data
Natural Language Processing
Not enough data
Not enough data
Semantic Analysis
Not enough data
Not enough data
Data Integration
Not enough data
Not enough data
Security
Not enough data
Not enough data
Not enough data
Not enough data
Model Training & Optimization - Active Learning Tools
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Data Management & Annotation - Active Learning Tools
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Model Performance & Analysis - Active Learning Tools
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Integration - Machine Learning
Not enough data
Not enough data
Learning - Machine Learning
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Categories
Categories
Shared Categories
Labellerr and V7 are categorized as Data Labeling, MLOps Platforms, and Data Science and Machine Learning Platforms
Unique Categories
Labellerr has no unique categories
V7 is categorized as Active Learning Tools, Intelligent Document Processing (IDP), OCR, Image Recognition, and Machine Learning
Reviews
Reviewers' Company Size
Labellerr
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
V7
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
Small-Business
(50 or fewer emp.)
Mid-Market
(51-1000 emp.)
Enterprise
(> 1000 emp.)
Reviewers' Industry
Information Technology and Services
33.3%
Computer Software
14.3%
Hospital & Health Care
9.5%
Public Relations and Communications
4.8%
Marketing and Advertising
4.8%
Other
33.3%
Information Technology and Services
25.5%
Computer Software
19.6%
Research
7.8%
Hospital & Health Care
5.9%
Industrial Automation
3.9%
Other
37.3%
Most Helpful Reviews
Labellerr
Most Helpful Favorable Review
Manu G.
Verified User in Education Management
The team is always available. They are responsive
Most Helpful Critical Review
Shaikh S.
Verified User in Computer Software
Nothing as of now. A good tool for annotation. Should have undo option.
V7
Most Helpful Favorable Review
Verified User in Computer & Network Security
It speeds up annotation. And it is really easy to get started
Most Helpful Critical Review
Verified User in Health, Wellness and Fitness
Large jump between Small and Medium pricing
Manu G.
Verified User in Education Management
The team is always available. They are responsive
Verified User in Computer & Network Security
It speeds up annotation. And it is really easy to get started
Shaikh S.
Verified User in Computer Software
Nothing as of now. A good tool for annotation. Should have undo option.
Verified User in Health, Wellness and Fitness
Large jump between Small and Medium pricing
Discussions
Labellerr has no discussions with answers
V7 has no discussions with answers
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