Compare Deepchecks and Encord 
At a Glance
Market Segments
Small-Business (50.0% of reviews)
Small-Business (52.5% of reviews)
Entry-Level Pricing
No pricing available
Contact Us
Deepchecks
Star Rating
(20)4.3 out of 5
Market Segments
Small-Business (50.0% of reviews)
Entry-Level Pricing
No pricing available
Learn more about DeepchecksEncord
Star Rating
(60)4.8 out of 5
Market Segments
Small-Business (52.5% of reviews)
Entry-Level Pricing
Contact Us
Learn more about EncordSummary
AI Generated Summary
AI-generated. Powered by real user reviews.
- Users report that Encord excels in Quality of Support, achieving a perfect score of 10.0, while Deepchecks falls behind with a score of 8.4. Reviewers mention that Encord's support team is highly responsive and knowledgeable, making it easier to resolve issues quickly.
- Reviewers mention that Encord offers superior Ease of Use with a score of 9.5 compared to Deepchecks' 8.5. Users on G2 highlight that Encord's intuitive interface simplifies the onboarding process, allowing teams to get started without extensive training.
- G2 users note that Encord's Model Training Efficiency is rated at 9.2, while Deepchecks scores lower at 9.0. Users say that Encord's streamlined model training process significantly reduces the time needed to deploy machine learning models.
- Users report that Encord shines in Human-in-the-Loop capabilities with a score of 9.8, whereas Deepchecks has not been rated in this area. Reviewers mention that this feature allows for better oversight and quality control during the data labeling process.
- Reviewers mention that Encord's Data Quality score of 9.6 is a strong point, while Deepchecks does not provide a comparable score. Users say that Encord's tools for data validation and error detection enhance the overall quality of the datasets used for training.
- Users on G2 highlight that Encord's Scalability is rated at 9.8, indicating it can handle growing data needs effectively, while Deepchecks scores 9.5. Reviewers mention that Encord's architecture allows for seamless scaling as projects expand, making it a reliable choice for long-term use.
Pricing
Entry-Level Pricing
Deepchecks
No pricing availableEncord
Simple and scalable pricing
Contact Us
Our pricing scales with your organization. Start building out your data annotation & active learning pipelines today.
- Computer vision labeling toolkit
- Model assisted labeling using your own models or our proprietary micro-models
- Automated object tracking and interpolation
Free Trial
Deepchecks
No trial information availableEncord
Free Trial is available
Ratings
Meets Requirements
9.1
19
9.3
45
Ease of Use
8.5
20
9.5
46
Ease of Setup
8.1
18
8.3
10
Ease of Admin
Not enough data
7.8
10
Quality of Support
8.5
18
10.0
44
Has the product been a good partner in doing business?
Not enough data
9.3
10
Product Direction (% positive)
7.7
20
9.7
45
Features by Category
Deployment
Not enough data
9.4
6
Not enough data
9.5
7
Not enough data
9.8
7
Not enough data
9.8
8
Not enough data
9.8
8
Deployment
Not enough data
10.0
6
Not enough data
9.5
7
Not enough data
9.5
7
Not enough data
9.6
8
Not enough data
10.0
8
Management
Not enough data
9.8
7
Not enough data
9.8
8
Not enough data
10.0
6
Not enough data
9.8
8
Operations
Not enough data
10.0
6
Not enough data
9.7
6
Not enough data
10.0
9
Management
Not enough data
10.0
7
Not enough data
10.0
8
Not enough data
9.8
7
Generative AI
Not enough data
Feature Not Available
Not enough data
Feature Not Available
Functionality
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Issue Resolution
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Management
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Generative AI
Not enough data
Not enough data
Not enough data
Not enough data
System
Not enough data
9.0
5
Not enough data
Not enough data
Not enough data
Not enough data
Model Development
Not enough data
Not enough data
Not enough data
9.7
6
Not enough data
10.0
5
Not enough data
9.7
6
Model Development
Not enough data
Not enough data
Not enough data
9.7
5
Not enough data
Not enough data
Machine/Deep Learning Services
Not enough data
9.5
7
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
9.7
5
Machine/Deep Learning Services
Not enough data
9.7
5
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
9.7
5
Deployment
Not enough data
10.0
7
Not enough data
9.8
7
Not enough data
9.5
7
Deployment
Not enough data
10.0
5
Not enough data
9.7
6
Not enough data
9.7
5
Generative AI
Not enough data
Feature Not Available
Not enough data
Feature Not Available
Not enough data
Feature Not Available
Quality
Not enough data
9.5
30
Not enough data
9.8
29
Not enough data
9.6
30
Not enough data
9.8
28
Automation
Not enough data
9.7
24
Not enough data
9.6
23
Image Annotation
Not enough data
9.6
29
Not enough data
9.4
26
Not enough data
9.1
22
Not enough data
9.7
23
Natural Language Annotation
Not enough data
9.7
13
Not enough data
10.0
13
Not enough data
9.9
15
Speech Annotation
Not enough data
9.9
13
Not enough data
9.9
12
Recognition Type
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
Feature Not Available
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Facial Recognition
Not enough data
Not enough data
Not enough data
Not enough data
Labeling
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Deployment
Not enough data
Not enough data
Model Training & Optimization - Active Learning Tools
9.2
10
Not enough data
9.0
10
Not enough data
8.8
10
Not enough data
8.5
10
Not enough data
8.7
10
Not enough data
Data Management & Annotation - Active Learning Tools
9.0
10
Not enough data
9.2
10
Not enough data
9.3
10
Not enough data
9.3
10
Not enough data
9.3
9
Not enough data
Model Performance & Analysis - Active Learning Tools
9.6
9
Not enough data
8.7
9
Not enough data
9.2
8
Not enough data
8.8
8
Not enough data
9.0
8
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
Deepchecks and Encord are categorized as Active Learning Tools
Unique Categories
Deepchecks is categorized as AIOps Platforms
Encord is categorized as Data Labeling, MLOps Platforms, Data Science and Machine Learning Platforms, Image Recognition, and Machine Learning
Reviews
Reviewers' Company Size
Deepchecks
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
Encord
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
20.0%
Consulting
10.0%
Computer Software
10.0%
Computer & Network Security
10.0%
Telecommunications
5.0%
Other
45.0%
Computer Software
37.3%
Medical Devices
11.9%
Hospital & Health Care
11.9%
Food & Beverages
10.2%
Medical Practice
5.1%
Other
23.7%
Most Helpful Reviews
Deepchecks
Most Helpful Favorable Review
Sayani C.
Verified User in Apparel & Fashion
Provides comphrehensive tools to evaluate.
Most Helpful Critical Review
John S.
Verified User in Real Estate
Data can be acquired easily which makes it easy for users
Encord
Most Helpful Favorable Review
Derrick M.
Verified User in Transportation/Trucking/Railroad
The platform is user-friendly to use for annotating videos. The user interface is easy to navigate, and the object detection annotation tools are very functional. The team is also very supportive and accommodating
Most Helpful Critical Review
Bipul T.
Verified User in Information Technology and Services
The zoom feature. Its working mechanism is exactly opposite compared to rest of the platforms in computer world. It could be better by not eliminating the opposite working mechanism.
Sayani C.
Verified User in Apparel & Fashion
Provides comphrehensive tools to evaluate.
Derrick M.
Verified User in Transportation/Trucking/Railroad
The platform is user-friendly to use for annotating videos. The user interface is easy to navigate, and the object detection annotation tools are very functional. The team is also very supportive and accommodating
John S.
Verified User in Real Estate
Data can be acquired easily which makes it easy for users
Bipul T.
Verified User in Information Technology and Services
The zoom feature. Its working mechanism is exactly opposite compared to rest of the platforms in computer world. It could be better by not eliminating the opposite working mechanism.
Discussions
Deepchecks has no discussions with answers
Encord has no discussions with answers
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