ML Model Validation / Testing Tools

Last update: December 27, 2024

Machine learning (ML) validation tools help users evaluate the model's performance against defined metrics and ensure the model is functioning as expected. +Show More

Machine learning (ML) validation tools help users evaluate the model's performance against defined metrics and ensure the model is functioning as expected. They generally provide monitoring and testing capabilities to validate ML models from training to production. Machine learning (ML) validation tools apply different methodologies and techniques to evaluate the quality of machine learning models, including:

Cross-validation: Assess how accurately a predictive model will perform in practice
Visualization: Illustrate the model's performance, and show correct and incorrect predictions
Data validation: Ensure the quality of data before it's used for training
Model Monitoring: Monitor your model in a production environment.

To be categorized as ML model validation tool, a product must:

Be able to compute a variety of performance metrics, such as recall, precision, or accuracy.
Monitor the performance of ML models. Include capabilities for checking the quality of the input data.

If you’d like to learn about the ecosystem consisting of ML Model Validation / Testing Tools and others, feel free to check AIMultiple Machine Learning.

How relevant, verifiable metrics drive AIMultiple’s rankings

AIMultiple uses relevant & verifiable metrics to evaluate vendors.

Metrics are selected based on typical enterprise procurement processes ensuring that market leaders, fast-growing challengers, feature-complete solutions and cost-effective solutions are ranked highly so they can be shortlisted.
Data regarding these metrics are collected from public sources as outlined in the “What are AIMultiple’s data sources?” section of this page.

There are 2 ways in which vendor metrics are processed to help prioritization:
1- Vendors are grouped within 4 metrics (customer satisfaction, market presence, growth and features) according to their performance in that metric.
2- Vendors that perform high in these metrics are ranked higher in the list.

The data used in each vendor’s ranking can be accessed by expanding the vendor’s row in the below list.
This page includes links to AIMultiple’s sponsors. Sponsored links are included in “Visit Website” buttons and ranked at the top of the list when results are sorted by “Sponsored”. Sponsors have no say over the ranking which is based on market data. Organic ranking can be seen by sorting by “AIMultiple” or other sorting approaches. For more on how AIMultiple works, please see the ethical standards that we follow and how we fund our research.

Products	Position	Customer satisfaction
Neptune AI	Leader	Satisfactory
Basis for Evaluation We made these evaluations based on the following parameters; Customer satisfaction Average rating 4.60 / 5 based on ~10 reviews Market presence Company's number of employees 50-100 employees Company's social media followers 30k-40k followers Total funding $10-50m # of funding rounds 3 Latest funding date April 12, 2022 Last funding amount $5-10m Company Type of company private Founding year 2017
Robust Intelligence	Leader	N/A
Basis for Evaluation We made these evaluations based on the following parameters; Customer satisfaction Average rating 4.50 / 5 based on 2 reviews
Kolena	Leader	N/A
Basis for Evaluation We made these evaluations based on the following parameters; Customer satisfaction Market presence Company's number of employees 30-40 employees Company's social media followers 2k-3k followers
Censius	Leader	N/A
Basis for Evaluation We made these evaluations based on the following parameters; Customer satisfaction Market presence Company's number of employees 10-20 employees Company's social media followers 10k-20k followers Company Type of company private Founding year 2020
Etiq AI	Leader	N/A
Basis for Evaluation We made these evaluations based on the following parameters; Customer satisfaction Market presence Company's number of employees 10-20 employees Company's social media followers 1k-2k followers Total funding $1-1m # of funding rounds 3 Latest funding date September 13, 2021 Last funding amount $100,000-250,000 Company Type of company private Founding year 2019
Deepchecks	Challenger	N/A
Basis for Evaluation We made these evaluations based on the following parameters; Customer satisfaction Market presence Company's number of employees 20-30 employees Company's social media followers 5k-10k followers Total funding $10-50m # of funding rounds 2 Latest funding date June 15, 2023 Last funding amount $10-50m Company Type of company private Founding year 2019
Snitch AI	Challenger	N/A
Basis for Evaluation We made these evaluations based on the following parameters; Customer satisfaction Market presence Company's number of employees 5-10 employees Company's social media followers 1k-2k followers Company Type of company private Founding year 2017

“-”: AIMultiple team has not yet verified that vendor provides the specified feature. AIMultiple team focuses on feature verification for top 10 vendors.

Sources

AIMultiple uses these data sources for ranking solutions and awarding badges in ML model validation / testing tools:

1 vendor web domains

1 social media profiles

4 search engine queries

Which one has collected the most reviews?

AIMultiple uses multiple datapoints in identifying market leaders:

Product line revenue (when available)
Number of reviews
Number of case studies
Number and experience of employees
Social media presence and engagement

Out of these, number of reviews information is available for all products and is summarized in the graph:

Neptune AI

Robust Intelligence

Deepchecks

Kolena

Etiq AI

What are the most mature ML model validation / testing tools?

Which one has the most employees?

Which ML model validation / testing tools companies have the most employees?

25 employees work for a typical company in this solution category which is 2 more than the number of employees for a typical company in the average solution category.

In most cases, companies need at least 10 employees to serve other businesses with a proven tech product or service. 5 companies with >10 employees are offering ml model validation / testing tools. Top 3 products are developed by companies with a total of 157 employees. The largest company in this domain is with more than 90 employees. provides the ML model validation / testing tools solution: Neptune AI

Insights

Where are ML model validation / testing tools vendors' HQs located?

Trends

What is the level of interest in ML model validation / testing tools?

This category was searched on average for 0 times per month on search engines in 2024. This number is still 0 in 2025. If we compare with other machine learning solutions, a typical solution was searched 3.6k times in 2024 and this decreased to 0 in 2025.

ML Model Validation / Testing Tools

Neptune AI

Basis for Evaluation

Customer satisfaction

Market presence

Company

Robust Intelligence

Basis for Evaluation

Customer satisfaction

Kolena

Basis for Evaluation

Customer satisfaction

Market presence

Censius

Basis for Evaluation

Customer satisfaction

Market presence

Company

Etiq AI

Basis for Evaluation

Customer satisfaction

Market presence

Company

Deepchecks

Basis for Evaluation

Customer satisfaction

Market presence

Company

Snitch AI

Basis for Evaluation

Customer satisfaction

Market presence

Company

Sources

Which one has collected the most reviews?

What are the most mature ML model validation / testing tools?

Which ML model validation / testing tools companies have the most employees?

Insights

Where are ML model validation / testing tools vendors' HQs located?

Trends

What is the level of interest in ML model validation / testing tools?

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