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Syntho

Syntho generates high-quality synthetic data, preserving privacy and accuracy, with extensive support for various sectors.
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Syntho Reviews

4.64
Based on 11 reviews
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Yuki Tanaka
Yuki Tanaka March 4, 2025

What do you like most about using Syntho?

I appreciate the high quality of synthetic data it generates. The accuracy and the way it mimics original datasets without exposing any sensitive information is impressive.

What do you dislike most about using Syntho?

The user interface could be more intuitive; sometimes, it takes a while to find specific features.

What problems does Syntho help you solve, and how does this benefit you?

Syntho allows us to develop and test our applications without worrying about data privacy issues. This significantly speeds up our development process.

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Dmitry Petrov
Dmitry Petrov February 27, 2025

What do you like most about using Syntho?

The synthetic mock data generation is incredibly useful for our testing phases, allowing us to simulate real-world scenarios.

What do you dislike most about using Syntho?

Sometimes the data generation process can be slow, especially when working with large datasets.

What problems does Syntho help you solve, and how does this benefit you?

It assists us in ensuring compliance with data privacy laws while still allowing us to innovate and create new solutions.

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Anwar Hussein
Anwar Hussein February 13, 2025

What do you like most about using Syntho?

I love the smart de-identification features. They work seamlessly, ensuring that no sensitive data leaks out.

What do you dislike most about using Syntho?

The pricing plans could be clearer; it took some time to figure out which plan suited our needs best.

What problems does Syntho help you solve, and how does this benefit you?

It allows us to create demos for our clients without revealing their actual data, which enhances trust and security in our services.

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Carlos Mendez
Carlos Mendez February 11, 2025

What do you like most about using Syntho?

The PII scanner is fantastic. It gives me peace of mind knowing that the generated data is safe and compliant with privacy regulations.

What do you dislike most about using Syntho?

Some advanced features require a steep learning curve for new users.

What problems does Syntho help you solve, and how does this benefit you?

It enables us to conduct thorough testing and analysis without compromising client data, which is crucial in the finance sector.

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Tariq Nasser
Tariq Nasser February 10, 2025

What do you like most about using Syntho?

I really like how it maintains the statistical properties of the original data, which is crucial for our analytics.

What do you dislike most about using Syntho?

It can be expensive for startups, so a more flexible pricing structure would be beneficial.

What problems does Syntho help you solve, and how does this benefit you?

It helps us in generating data for testing new algorithms, thus allowing for faster innovation without compromising user privacy.

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Sofia Ivanova
Sofia Ivanova February 8, 2025

What do you like most about using Syntho?

The ability to generate time-series data is a game-changer for our analytics projects. It allows for more accurate modeling.

What do you dislike most about using Syntho?

Occasionally, the quality assurance reports can be a bit overwhelming with too much information.

What problems does Syntho help you solve, and how does this benefit you?

It helps in generating realistic datasets for healthcare research while ensuring patient data confidentiality, which is paramount.

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Zara Al-Farsi
Zara Al-Farsi February 7, 2025

What do you like most about using Syntho?

The extensive documentation is a valuable resource. It helped me get up to speed quickly on how to use the platform effectively.

What do you dislike most about using Syntho?

The initial setup process was a bit complicated and could be streamlined.

What problems does Syntho help you solve, and how does this benefit you?

It allows us to create datasets for machine learning training without risking our users' data privacy, making it invaluable for our AI projects.

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Aisha Khan
Aisha Khan January 20, 2025

What do you like most about using Syntho?

The platform's versatility across sectors like healthcare and finance is remarkable. It adapts well to our varying needs.

What do you dislike most about using Syntho?

The support response time can sometimes be slow, which is frustrating when we're in a crunch.

What problems does Syntho help you solve, and how does this benefit you?

It allows us to generate mock datasets for training our staff without risking sensitive information, which is a big plus for compliance.

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Liam O'Sullivan
Liam O'Sullivan January 19, 2025

What do you like most about using Syntho?

The quality assurance feature is top-notch. It provides a comprehensive overview of data integrity, which is essential for our projects.

What do you dislike most about using Syntho?

While it's generally user-friendly, some features are buried under layers of menus.

What problems does Syntho help you solve, and how does this benefit you?

It helps our team generate synthetic data for machine learning models without the risk of exposing real user data, thus speeding up our analysis.

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Mateo Sanchez
Mateo Sanchez January 15, 2025

What do you like most about using Syntho?

The ability to de-identify data while keeping it usable is phenomenal. It’s a big win for data compliance.

What do you dislike most about using Syntho?

The loading times can be a bit long, especially when generating large datasets.

What problems does Syntho help you solve, and how does this benefit you?

It helps us in conducting experiments with high-quality data without exposing real user information, which is critical in our field.

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Nina Schmidt
Nina Schmidt January 10, 2025

What do you like most about using Syntho?

The customer support is outstanding. Any issues I've had were resolved quickly and efficiently.

What do you dislike most about using Syntho?

The integration with existing systems could be smoother.

What problems does Syntho help you solve, and how does this benefit you?

It allows us to create high-quality synthetic datasets for testing our models, which is essential for our research in data science.

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