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Compare Clarifai and Microsoft Computer Vision API 
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At a Glance
Market Segments
Small-Business (61.5% of reviews)
Small-Business (47.8% of reviews)
Entry-Level Pricing
Free 1000 operations
No pricing available
Clarifai
Star Rating
(65)4.3 out of 5
Market Segments
Small-Business (61.5% of reviews)
Entry-Level Pricing
Free 1000 operations
Browse all 4 pricing plansMicrosoft Computer Vision API
Star Rating
(47)4.1 out of 5
Market Segments
Small-Business (47.8% of reviews)
Entry-Level Pricing
No pricing available
Learn more about Microsoft Computer Vision APISummary
AI Generated Summary
AI-generated. Powered by real user reviews.
- Users report that Microsoft Computer Vision API excels in Object Detection with a score of 9.0, making it a preferred choice for applications requiring precise identification of objects in images. In contrast, Clarifai also performs well in this area but has a slightly lower score of 8.2, indicating that Microsoft may offer a more robust solution for users focused on object recognition.
- Reviewers mention that Clarifai shines in Pre-Built Algorithms, scoring 9.3, which allows users to quickly implement solutions without extensive customization. Microsoft Computer Vision API, while still strong, has a score of 9.2, suggesting that Clarifai may provide a more extensive library of ready-to-use algorithms for rapid deployment.
- G2 users highlight that Microsoft Computer Vision API has a superior AI Inference Speed with a score of 9.1, which is crucial for applications requiring real-time processing. Clarifai, while competitive, has a lower score in this area, indicating that users may experience slower response times when using its services.
- Users on G2 report that Clarifai offers better Ease of Admin with a score of 8.7 compared to Microsoft Computer Vision API's 8.3. This suggests that Clarifai may provide a more user-friendly administrative experience, making it easier for teams to manage their projects.
- Reviewers mention that Microsoft Computer Vision API has a strong focus on Data Quality, scoring 8.8, which is essential for ensuring accurate results in machine learning tasks. Clarifai also performs well in this area but does not quite match the quality offered by Microsoft, indicating a potential advantage for users prioritizing data integrity.
- Users say that both products have comparable Quality of Support, each scoring 8.3, but some users have noted that Clarifai's support is slightly more responsive, which can be a deciding factor for businesses that require timely assistance.
Pricing
Entry-Level Pricing
Clarifai
Clarifai Community
Free
1000 operations
We offer a free version of our platform for our community to discover, develop and share models, workflows, and datasets.
- Access to 100s of models from Clarifai, Facebook, Google, Hugging Face, Microsoft, Princeton NLP, Salesforce
- Easy UI with a “drag-n-drop” workflow graph editor
- Access to community shared workflows, datasets, and apps
Microsoft Computer Vision API
No pricing availableFree Trial
Clarifai
Free Trial is available
Microsoft Computer Vision API
No trial information availableRatings
Meets Requirements
8.2
58
8.5
38
Ease of Use
8.2
58
8.2
39
Ease of Setup
7.7
35
8.2
38
Ease of Admin
8.8
20
8.3
35
Quality of Support
8.1
49
8.3
33
Has the product been a good partner in doing business?
8.5
18
8.3
35
Product Direction (% positive)
7.8
53
7.9
38
Features by Category
System
8.4
17
Not enough data
Model Development
8.7
18
Not enough data
7.8
18
Not enough data
9.2
18
Not enough data
8.4
18
Not enough data
Model Development
8.8
15
Not enough data
Machine/Deep Learning Services
8.7
18
Not enough data
9.1
16
Not enough data
8.4
16
Not enough data
8.4
17
Not enough data
Machine/Deep Learning Services
8.8
16
Not enough data
8.5
16
Not enough data
Deployment
8.2
17
Not enough data
8.0
17
Not enough data
8.0
15
Not enough data
Generative AI
8.8
15
Not enough data
8.7
15
Not enough data
8.3
15
Not enough data
Agentic AI - Data Science and Machine Learning Platforms
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
Not enough data
Not enough data
Not enough data
Not enough data
Quality
8.3
13
Not enough data
8.7
13
Not enough data
8.9
12
Not enough data
8.1
12
Not enough data
Automation
7.9
12
Not enough data
7.8
12
Not enough data
Image Annotation
7.9
11
Not enough data
8.3
12
Not enough data
8.3
11
Not enough data
8.3
11
Not enough data
Natural Language Annotation
7.9
11
Not enough data
8.1
9
Not enough data
7.8
9
Not enough data
Speech Annotation
7.3
8
Not enough data
7.7
8
Not enough data
Recognition Type
8.3
12
Not enough data
9.1
15
Not enough data
8.7
14
Not enough data
7.6
12
Not enough data
8.1
12
Not enough data
7.8
13
Not enough data
8.2
11
Not enough data
7.9
13
Not enough data
Facial Recognition
8.5
13
Not enough data
7.8
12
Not enough data
Labeling
8.3
12
Not enough data
8.6
12
Not enough data
9.1
13
Not enough data
Deployment
8.6
13
Not enough data
Scalability and Performance - Generative AI Infrastructure
8.4
22
Not enough data
8.1
21
Not enough data
9.0
21
Not enough data
Cost and Efficiency - Generative AI Infrastructure
7.9
22
Not enough data
8.4
20
Not enough data
Feature Not Available
Not enough data
Integration and Extensibility - Generative AI Infrastructure
8.1
19
Not enough data
7.9
20
Not enough data
8.5
21
Not enough data
Security and Compliance - Generative AI Infrastructure
8.8
19
Not enough data
8.5
19
Not enough data
Feature Not Available
Not enough data
Usability and Support - Generative AI Infrastructure
7.9
20
Not enough data
Feature Not Available
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
Large Language Model Operationalization (LLMOps)Hide 15 FeaturesShow 15 Features
Not enough data
Not enough data
Prompt Engineering - Large Language Model Operationalization (LLMOps)
Not enough data
Not enough data
Not enough data
Not enough data
Inference Optimization - Large Language Model Operationalization (LLMOps)
Not enough data
Not enough data
Model Garden - Large Language Model Operationalization (LLMOps)
Not enough data
Not enough data
Custom Training - Large Language Model Operationalization (LLMOps)
Not enough data
Not enough data
Application Development - Large Language Model Operationalization (LLMOps)
Not enough data
Not enough data
Model Deployment - Large Language Model Operationalization (LLMOps)
Not enough data
Not enough data
Not enough data
Not enough data
Guardrails - Large Language Model Operationalization (LLMOps)
Not enough data
Not enough data
Not enough data
Not enough data
Model Monitoring - Large Language Model Operationalization (LLMOps)
Not enough data
Not enough data
Not enough data
Not enough data
Security - Large Language Model Operationalization (LLMOps)
Not enough data
Not enough data
Not enough data
Not enough data
Gateways & Routers - Large Language Model Operationalization (LLMOps)
Not enough data
Not enough data
Usability - Emotion AI
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Performance Optimization - Emotion AI
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Security & Compliance - Emotion AI
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Advanced Features - Emotion AI
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Detection Features - Emotion AI
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Agentic AI - Emotion AI
Not enough data
Not enough data
Not enough data
Not enough data
Data Ingestion & Preparation - Low-Code Machine Learning Platforms
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Model Construction & Automation - Low-Code Machine Learning Platforms
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Categories
Categories
Shared Categories
Clarifai and Microsoft Computer Vision API are categorized as Image Recognition
Unique Categories
Microsoft Computer Vision API has no unique categories
Reviews
Reviewers' Company Size
Clarifai
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
Microsoft Computer Vision API
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
Computer Software
23.1%
Information Technology and Services
12.3%
Higher Education
9.2%
Education Management
4.6%
Online Media
3.1%
Other
47.7%
Hospital & Health Care
13.0%
Marketing and Advertising
8.7%
Public Relations and Communications
6.5%
Writing and Editing
4.3%
Information Technology and Services
4.3%
Other
63.0%
Alternatives
Discussions
Clarifai has no discussions with answers
Microsoft Computer Vision API has no discussions with answers
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