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Compare Aporia and WhyLabs 
At a Glance
Market Segments
Small-Business (55.9% of reviews)
Small-Business (48.1% of reviews)
Entry-Level Pricing
Contact Us Per Year
Free
Aporia
Star Rating
(68)4.8 out of 5
Market Segments
Small-Business (55.9% of reviews)
Pros & Cons
Entry-Level Pricing
Contact Us Per Year
Browse all 2 pricing plansWhyLabs
Star Rating
(27)4.6 out of 5
Market Segments
Small-Business (48.1% of reviews)
Pros & Cons
Entry-Level Pricing
Free
Browse all 4 pricing plansAporia vs WhyLabs
When assessing the two solutions, reviewers found Aporia easier to use and set up. However, reviewers felt that administration of both products was equally easy, and preferred doing business with WhyLabs overall.
- Reviewers felt that Aporia meets the needs of their business better than WhyLabs.
- When comparing quality of ongoing product support, reviewers felt that WhyLabs is the preferred option.
- For feature updates and roadmaps, our reviewers preferred the direction of WhyLabs over Aporia.
Pricing
Entry-Level Pricing
Aporia
Scaler
Contact Us
Per Year
For ML teams with multiple production models
- Everything included in ML Starter
- Unlimited rows and predictions
- Unlimited users
WhyLabs
Starter
Free
ML and Data Monitoring for individuals
- Up to 200 features or columns/Project
- Five segments/Project
- 10M predictions/month
Free Trial
Aporia
Free Trial is available
WhyLabs
Free Trial is available
Ratings
Meets Requirements
9.3
57
8.9
25
Ease of Use
9.2
59
8.5
25
Ease of Setup
9.3
21
8.7
17
Ease of Admin
9.1
13
9.1
13
Quality of Support
9.5
54
9.7
25
Has the product been a good partner in doing business?
9.5
13
9.7
11
Product Direction (% positive)
9.6
59
10.0
25
Features by Category
Deployment
8.7
29
8.3
17
8.9
31
8.9
19
9.0
26
7.5
17
8.5
28
8.1
19
9.0
29
8.1
18
Deployment
8.7
30
8.1
18
9.0
32
8.9
20
8.8
28
7.7
17
9.0
32
8.3
20
9.1
31
8.3
21
Management
8.7
26
7.6
16
9.3
29
9.3
21
8.7
28
8.0
15
8.8
26
7.2
15
Operations
9.0
34
9.1
19
8.7
29
8.1
16
8.6
28
8.4
18
Management
8.7
26
8.1
15
9.2
31
9.5
20
8.7
29
8.5
16
Generative AI
9.4
6
8.2
12
9.2
6
8.2
12
Scalability and Performance - Generative AI Infrastructure
9.7
11
Not enough data
9.2
11
Not enough data
9.5
11
Not enough data
Cost and Efficiency - Generative AI Infrastructure
8.8
11
Not enough data
9.2
11
Not enough data
9.5
11
Not enough data
Integration and Extensibility - Generative AI Infrastructure
8.8
11
Not enough data
9.2
11
Not enough data
9.5
11
Not enough data
Security and Compliance - Generative AI Infrastructure
9.5
11
Not enough data
8.9
11
Not enough data
9.2
11
Not enough data
Usability and Support - Generative AI Infrastructure
9.7
11
Not enough data
8.8
11
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
Categories
Categories
Shared Categories
Aporia and WhyLabs are categorized as MLOps Platforms
Unique Categories
Aporia is categorized as Large Language Model Operationalization (LLMOps) and Generative AI Infrastructure
WhyLabs has no unique categories
Reviews
Reviewers' Company Size
Aporia
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
WhyLabs
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
20.6%
Information Technology and Services
11.8%
Computer & Network Security
10.3%
Financial Services
5.9%
Telecommunications
4.4%
Other
47.1%
Information Technology and Services
25.9%
Computer Software
18.5%
Financial Services
14.8%
Consulting
7.4%
Internet
7.4%
Other
25.9%
Alternatives
Discussions
Aporia has no discussions with answers
WhyLabs has no discussions with answers
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