# Best Synthetic Data Tools

## How Many Synthetic Data Tools Products Does G2 Track?

**Total Products under this Category:** 82

### Category Stats (Aug 2026)

- **Average Rating:** 4.38/5 The average rating of products in this category, based on all submitted ratings
- **Top Trending Product:** K2View (+0.44%) - Among all products in this category, K2View recorded the largest rating increase compared to last month

_Last updated: August 04, 2026_

## How Does G2 Rank Synthetic Data Tools Products?

**Why You Can Trust G2's Software Rankings:**

- 30 Analysts and Data Experts
- 500+ Authentic Reviews
- 82+ Products
- Unbiased Rankings

G2's software rankings are built on verified user reviews, rigorous moderation, and a consistent research methodology maintained by a team of analysts and data experts. Each product is measured using the same transparent criteria, with no paid placement or vendor influence. While reviews reflect real user experiences, which can be subjective, they offer valuable insight into how software performs in the hands of professionals. Together, these inputs power the G2 Score, a standardized way to compare tools within every category.

## G2 Grid® for Synthetic Data Tools
 ![G2 Grid® for Synthetic Data Tools plotting products by satisfaction and market presence](https://www.g2.com/categories/synthetic-data/grids.png?focus%5B%5D=1308795&focus%5B%5D=127779&focus%5B%5D=160313&focus%5B%5D=128717&focus%5B%5D=161807&focus%5B%5D=71319&focus%5B%5D=162864&focus%5B%5D=1314021)

Highlighted products: IBM watsonx.ai, Tonic.ai, Tumult Analytics, YData, Gretel.ai, CA Test Data Manager, Syntheticus.ai | Synthetic Data Generator, and KopiKat.

Underlying data: [Grid® JSON](https://www.g2.com/categories/synthetic-data/grids.json?focus%5B%5D=ibm-watsonx-ai&focus%5B%5D=tonic-ai&focus%5B%5D=tumult-analytics&focus%5B%5D=ydata&focus%5B%5D=gretel-ai&focus%5B%5D=ca-test-data-manager&focus%5B%5D=syntheticus-ai-synthetic-data-generator&focus%5B%5D=kopikat)

**Sponsored**

### Amazon SageMaker

Amazon SageMaker is a fully managed service that enables data scientists and developers to build, train, and deploy machine learning (ML) models at scale. It provides a comprehensive suite of tools and infrastructure, streamlining the entire ML workflow from data preparation to model deployment. With SageMaker, users can quickly connect to training data, select and optimize algorithms, and deploy models in a secure and scalable environment. Key Features and Functionality: - Integrated Development Environments (IDEs): SageMaker offers a unified, web-based interface with built-in IDEs, including JupyterLab and RStudio, facilitating seamless development and collaboration. - Pre-built Algorithms and Frameworks: It includes a selection of optimized ML algorithms and supports popular frameworks like TensorFlow, PyTorch, and Apache MXNet, allowing flexibility in model development. - Automated Model Tuning: SageMaker can automatically tune models to achieve optimal accuracy, reducing the time and effort required for manual adjustments. - Scalable Training and Deployment: The service manages the underlying infrastructure, enabling efficient training of models on large datasets and deploying them across auto-scaling clusters for high availability. - MLOps and Governance: SageMaker provides tools for monitoring, debugging, and managing ML models, ensuring robust operations and compliance with enterprise security standards. Primary Value and Problem Solved: Amazon SageMaker addresses the complexity and resource-intensive nature of developing and deploying ML models. By offering a fully managed environment with integrated tools and scalable infrastructure, it accelerates the ML lifecycle, reduces operational overhead, and enables organizations to derive insights and value from their data more efficiently. This empowers businesses to innovate rapidly and implement AI solutions without the need for extensive in-house expertise or infrastructure management.

[Visit website](https://www.g2.com/external_clickthroughs/record?secure%5Bad_program%5D=ppc&secure%5Bad_slot%5D=category_product_list_llm&secure%5Bcategory_id%5D=2433&secure%5Bchosen_at%5D=2026-08-05T01%3A01%3A55Z&secure%5Bdisplayable_resource_id%5D=2433&secure%5Bdisplayable_resource_type%5D=Category&secure%5Bmedium%5D=sponsored&secure%5Bplacement_reason%5D=page_category&secure%5Bplacement_resource_ids%5D%5B%5D=2433&secure%5Bprioritized%5D=false&secure%5Bproduct_id%5D=52115&secure%5Bresource_id%5D=2433&secure%5Bresource_type%5D=Category&secure%5Bsource_type%5D=category_page&secure%5Bsource_url%5D=https%3A%2F%2Fwww.g2.com%2Fcategories%2Fsynthetic-data%3Fopen_modal_url%3D%252Fproducts%252Fgretel-ai%252Fwishlists%253Fhost_path%253D%25252Fcategories%25252Fsynthetic-data%2526source%253Dcategory&secure%5Btoken%5D=00b19b5812727df6a34de6252153a9760e27569a4f0ab054c56bbfde87fdba03&secure%5Burl%5D=https%3A%2F%2Faws.amazon.com%2Fsagemaker%2F%3Ftrk%3De054ba95-b51d-4594-98bc-aa0239b1797a%26sc_channel%3Ddisplay%2Bads&secure%5Burl_type%5D=custom_url)

### [IBM watsonx.ai](https://www.g2.com/products/ibm-watsonx-ai/reviews)

Watsonx.ai is part of the IBM watsonx platform that brings together new generative AI capabilities, powered by foundation models and traditional machine learning into a powerful studio spanning the AI lifecycle. With watsonx.ai, you can build, train, validate, tune and deploy generative AI, foundation models and machine learning capabilities with ease and build AI applications in a fraction of the time with a fraction of the data.

**Average Rating:** 4.4/5.0

**Total Reviews:** 139

#### Who Is the Company Behind IBM watsonx.ai?

- **Seller:** [IBM](https://www.g2.com/sellers/ibm)
- **Company Website:** www.ibm.com
- **Year Founded:** 1911
- **HQ Location:** Armonk, New York, United States
- **Twitter:** @IBMSecurity  
74,660 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=14b544adaece4fdbc987f1d7f7028048c22259946811200cc751263825586af9&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F1009%2F&secure%5Burl_type%5D=linkedin_company_website)  
328,202 employees on LinkedIn®

#### Who Uses This Product?

- **Who Uses This:** Consultant
- **Top Industries:** Information Technology and Services, Computer Software
- **Company Size:** 41% Small, 32% Large

#### What Do G2 Reviewers Say About IBM watsonx.ai?

_AI-generated summary from verified user reviews_

##### Pros

- Users appreciate the **ease of use** in IBM watsonx.ai, facilitating quicker AI integration and effective management.
- Users appreciate the **model variety** of IBM watsonx.ai, enabling customized training on existing models for enhanced performance.
- Users appreciate the **seamless integration of enterprise-grade AI** in IBM watsonx.ai, enhancing decision-making and workflow efficiency.
- Users appreciate the **enterprise-grade integrated studio** of IBM watsonx.ai for seamless AI training and reliable insights.
- Users value the **enterprise-grade AI integration** of IBM watsonx.ai, enhancing decision-making and business operations efficiently.

##### Cons

- Users find the **difficult learning** curve of IBM watsonx.ai daunting, making it less accessible for newcomers and smaller teams.
- Users find the **complex setup** of IBM watsonx.ai challenging, making it less suitable for small teams and beginners.
- Users find the **steep learning curve** of IBM watsonx.ai challenging, making it less accessible for non-technical teams.
- Users find the product **expensive** and challenging for small teams, citing high costs and complex setup requirements.
- Users find the **complex setup** of IBM watsonx.ai challenging, especially for beginners and small teams.

#### What Are Recent G2 Reviews of IBM watsonx.ai?

**["Comprehensive One-Stop Platform for Building and Testing AI Workflows"](https://www.g2.com/survey_responses/ibm-watsonx-ai-review-13196706)**

**Rating:** 4.0/5.0 stars

_— Manish D._

[Read full review](https://www.g2.com/survey_responses/ibm-watsonx-ai-review-13196706)

**["Unified, Governed AI Studio with Strong Performance and Seamless IBM Integrations"](https://www.g2.com/survey_responses/ibm-watsonx-ai-review-13184421)**

**Rating:** 4.0/5.0 stars

_— Manan S._

[Read full review](https://www.g2.com/survey_responses/ibm-watsonx-ai-review-13184421)

### [Tonic.ai](https://www.g2.com/products/tonic-ai/reviews)

Tonic.ai frees developers to build with safe, high-fidelity synthetic data to accelerate software and AI innovation while protecting data privacy. Through industry-leading solutions for data synthesis, de-identification, and subsetting, our products enable on-demand access to realistic structured, semi-structured, and unstructured data for software development, testing, and AI model training. The product suite includes: - Tonic Fabricate for AI-powered synthetic data from scratch - Tonic Structural for modern test data management - Tonic Textual for unstructured data redaction and synthesis. Unblock innovation, eliminate collisions in testing, accelerate your engineering velocity, and ship better products, all while safeguarding data privacy. Founded in 2018, with offices in San Francisco, Atlanta, New York, and London, the company is pioneering enterprise tools for data synthesis and de-identification in pursuit of its mission to unblock innovation with usable data. Thousands of developers use data generated with the Tonic.ai platform on a daily basis to build products and train models faster in industries as wide ranging as healthcare, financial services, insurance, logistics, edtech, and e-commerce. Working with customers like Comcast, eBay, UnitedHealthcare, and Fidelity Investments, Tonic.ai builds developer solutions to advance its goals of advocating for the privacy of individuals while enabling companies to do their best work. Be free to build with high-fidelity synthetic data for software and AI development.

**Average Rating:** 4.2/5.0

**Total Reviews:** 38

#### Who Is the Company Behind Tonic.ai?

- **Seller:** [Tonic.ai](https://www.g2.com/sellers/tonic-ai)
- **Year Founded:** 2018
- **HQ Location:** San Francisco, California
- **Twitter:** @tonicfakedata  
698 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=37f7574472c5ef652000379b35295af9c67e86a59000aa1a99ab5e8551fd955f&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F18621512&secure%5Burl_type%5D=linkedin_company_website)  
104 employees on LinkedIn®

#### Who Uses This Product?

- **Top Industries:** Computer Software, Financial Services
- **Company Size:** 45% Medium, 32% Small

#### What Are Recent G2 Reviews of Tonic.ai?

**["Reliable anonymisation of unstructured text without losing context"](https://www.g2.com/survey_responses/tonic-ai-review-12025321)**

**Rating:** 4.5/5.0 stars

_— Ankit S._

[Read full review](https://www.g2.com/survey_responses/tonic-ai-review-12025321)

**["Exceptional Test Data Generation for Safe, Realistic Debugging"](https://www.g2.com/survey_responses/tonic-ai-review-11913479)**

**Rating:** 5.0/5.0 stars

_— Verified User in Financial Services_

[Read full review](https://www.g2.com/survey_responses/tonic-ai-review-11913479)

### [Tumult Analytics](https://www.g2.com/products/tumult-analytics/reviews)

Tumult Analytics is an advanced, open-source Python library designed to facilitate the deployment of differential privacy in data analysis. It enables organizations to generate statistical summaries from sensitive datasets while ensuring individual privacy is maintained. Trusted by institutions such as the U.S. Census Bureau, the Wikimedia Foundation, and the Internal Revenue Service, Tumult Analytics offers a robust and scalable solution for privacy-preserving data analysis. Key Features and Functionality: - Robust and Production-Ready: Developed and maintained by a team of differential privacy experts, Tumult Analytics is built for production environments and has been implemented by major institutions. - Scalable: Operating on Apache Spark, it efficiently processes datasets containing billions of rows, making it suitable for large-scale data analysis tasks. - User-Friendly APIs: The platform provides Python APIs that are familiar to users of Pandas and PySpark, facilitating easy adoption and integration into existing workflows. - Comprehensive Functionality: It supports a wide array of aggregation functions, data transformation operators, and privacy definitions, allowing for flexible and powerful data analysis under multiple privacy models. Primary Value and Problem Solved: Tumult Analytics addresses the critical challenge of extracting valuable insights from sensitive data without compromising individual privacy. By implementing differential privacy, it ensures that the risk of re-identification is minimized, enabling organizations to share and analyze data responsibly. This capability is particularly vital for sectors handling sensitive information, such as public institutions, healthcare, and finance, where maintaining data privacy is both a regulatory requirement and an ethical obligation.

**Average Rating:** 4.4/5.0

**Total Reviews:** 38

#### Who Is the Company Behind Tumult Analytics?

- **Seller:** [Tumult Labs, Inc.](https://www.g2.com/sellers/tumult-labs-inc)
- **Year Founded:** 2019
- **HQ Location:** Durham
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=82b33861a6440e7a81538c24e0f6029768bdd3af543f5f5a0f1577f069ab29f0&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Ftmltlabs&secure%5Burl_type%5D=linkedin_company_website)  
3 employees on LinkedIn®

#### Who Uses This Product?

- **Top Industries:** Information Technology and Services
- **Company Size:** 50% Small, 32% Medium

#### What Are Recent G2 Reviews of Tumult Analytics?

**["Aggregating Statistics made easy with privacy and prod ready framework"](https://www.g2.com/survey_responses/tumult-analytics-review-11461269)**

**Rating:** 5.0/5.0 stars

_— Jai A._

[Read full review](https://www.g2.com/survey_responses/tumult-analytics-review-11461269)

**["A Friendly and Highly Secure platform"](https://www.g2.com/survey_responses/tumult-analytics-review-10303460)**

**Rating:** 5.0/5.0 stars

_— Swathi K._

[Read full review](https://www.g2.com/survey_responses/tumult-analytics-review-10303460)

### [YData](https://www.g2.com/products/ydata/reviews)

YData helps data science teams build better datasets for AI

**Average Rating:** 4.6/5.0

**Total Reviews:** 12

#### Who Is the Company Behind YData?

- **Seller:** [YData](https://www.g2.com/sellers/ydata)
- **Year Founded:** 2019
- **HQ Location:** Seattle, WA
- **Twitter:** @YData\_ai  
685 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=05da33dae69c4451858c1f8ea286ebc794943198d53cdbc188d11c9ef425b206&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fydataai&secure%5Burl_type%5D=linkedin_company_website)  
41 employees on LinkedIn®

#### Who Uses This Product?

- **Company Size:** 67% Medium, 25% Small

#### What Are Recent G2 Reviews of YData?

**["YData for Smarter Workflows"](https://www.g2.com/survey_responses/ydata-review-10429600)**

**Rating:** 5.0/5.0 stars

_— Archita G._

[Read full review](https://www.g2.com/survey_responses/ydata-review-10429600)

**["Reliable data means YData"](https://www.g2.com/survey_responses/ydata-review-10019929)**

**Rating:** 5.0/5.0 stars

_— RAKESH S._

[Read full review](https://www.g2.com/survey_responses/ydata-review-10019929)

#### What Are G2 Users Discussing About YData?

- [What is YData used for?](https://www.g2.com/discussions/what-is-ydata-used-for) - 1 comment

## FAQs About Synthetic Data Tools

Generated using AI

Last updated: June 3, 2026

### Synthetic data generators with schema inference that reduce setup time from hours to minutes software

According to verified users, tools in this category can reduce setup work when they automate schema discovery, data modeling, and dataset provisioning. Recent reviews frequently mention auto-discovery catalogs, easier relationship building across databases, and workflows that replace manual scripting or large database clones. Buyers also call out faster access to realistic, compliant datasets for development and QA, especially when teams need entity-based subsets instead of full copies. The strongest review themes emphasize quicker onboarding, cleaner interfaces, and structured workflows, though some users note that complex environments still require effort during first-time configuration and modeling.

### Synthetic data tools for testing ML models with realistic patterns without production data exposure

According to verified users, synthetic data tools help ML and AI teams test, train, and validate models without relying on live production records. Reviews consistently describe value in creating realistic datasets that preserve useful patterns while protecting sensitive information through anonymization, de-identification, masking, or privacy controls. Buyers mention this is especially helpful for debugging, experimentation, fine-tuning, and sandbox testing, where teams need safe data that still reflects real business conditions. Across the recent review set, the main benefits are reduced privacy risk, less manual dummy-data creation, and faster experimentation, while common cautions include learning curves, setup complexity, and occasional limits with large or highly complex datasets.

### Synthetic data tools providing granular controls over masking rules for different PII categories

According to verified users, granular masking controls matter most when teams must protect different kinds of sensitive data without making test datasets unusable. Recent reviews highlight automated in-flight masking, compliant data preparation, anonymization workflows, and privacy-preserving dataset generation for development, QA, and AI training. Buyers value tools that let them keep realistic structure, business context, and referential integrity while still limiting exposure of customer or regulated information. The review set suggests that stronger masking and governance capabilities are particularly important in enterprise and high-stakes environments, although some users say advanced configuration, documentation depth, and technical setup can affect how quickly teams realize value.

### What are synthetic data tools

Synthetic data tools are platforms that help teams create realistic datasets for testing, development, analytics, or AI work without depending on direct use of production data. In recent G2 reviews, users describe them as useful for generating safe test data, anonymizing sensitive records, masking private information, preserving referential integrity, and speeding up data access for lower environments. Reviewers also connect this category with schema discovery, self-service provisioning, workflow automation, and support for model training or experimentation. The common thread is enabling teams to work with data that remains usable and business-relevant while reducing privacy, compliance, and operational friction.

### How do teams use Synthetic Data for testing workflows

G2 reviewers mention that teams use synthetic data in testing workflows to provision realistic datasets faster, support QA, debug code, and validate end-to-end scenarios without moving full production copies across environments. Recent reviews describe self-service access to specific data sets, entity-based subsets that preserve relationships, and repeatable preparation processes that reduce manual work before development can begin. Users also mention loading production-like data into test environments alongside synthetic generation, which helps maintain business context while protecting sensitive records. The main workflow advantage is faster delivery with fewer delays tied to approvals, privacy concerns, or hand-built dummy data.

### [Gretel.ai](https://www.g2.com/products/gretel-ai/reviews)

Our mission is to enable developers to safely and quickly experiment, collaborate, and build with data.

**Average Rating:** 4.4/5.0

**Total Reviews:** 13

#### Who Is the Company Behind Gretel.ai?

- **Seller:** [Gretel.ai](https://www.g2.com/sellers/gretel-ai)
- **Year Founded:** 2020
- **HQ Location:** Palo Alto, US
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=36c47b01619742da49f7420a6371b4e7ca8b151137ef3f30b222b3e22570f149&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F51732380&secure%5Burl_type%5D=linkedin_company_website)  
40 employees on LinkedIn®

#### Who Uses This Product?

- **Company Size:** 77% Medium, 23% Small

#### What Are Recent G2 Reviews of Gretel.ai?

**["Helps me most when I have to mask my sensitive info but still convey the gist"](https://www.g2.com/survey_responses/gretel-ai-review-10008219)**

**Rating:** 4.0/5.0 stars

_— Monica B._

[Read full review](https://www.g2.com/survey_responses/gretel-ai-review-10008219)

**["Amazing platform to use and generate AI data set for AI module"](https://www.g2.com/survey_responses/gretel-ai-review-9983552)**

**Rating:** 5.0/5.0 stars

_— Antonietta C._

[Read full review](https://www.g2.com/survey_responses/gretel-ai-review-9983552)

### [CA Test Data Manager](https://www.g2.com/products/ca-test-data-manager/reviews)

CA Test Data Manager uniquely combines elements of data subsetting, masking, synthetic, cloning and on-demand data generation to enable testing teams to meet the agile testing needs of their organization. This solution automates one of the most time-consuming and resource-intensive problems in Continuous Delivery: the creating, maintaining and provisioning of the test data needed to rigorously test evolving applications.

**Average Rating:** 4.0/5.0

**Total Reviews:** 21

#### Who Is the Company Behind CA Test Data Manager?

- **Seller:** [Broadcom](https://www.g2.com/sellers/broadcom-ab3091cd-4724-46a8-ac89-219d6bc8e166)
- **Year Founded:** 1991
- **HQ Location:** San Jose, CA
- **Twitter:** @broadcom  
63,909 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=093adce8015fea9ef126312884b465dc8e3c20e17dcb12fbb77a7bd82577e7a5&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fbroadcom%2F&secure%5Burl_type%5D=linkedin_company_website)  
55,094 employees on LinkedIn®
- **Ownership:** NASDAQ: CA

#### Who Uses This Product?

- **Top Industries:** Banking, Accounting
- **Company Size:** 48% Small, 33% Large

#### What Are Recent G2 Reviews of CA Test Data Manager?

**["CA TDM: A wonderful Test Data Management tool for all your TDM needs"](https://www.g2.com/survey_responses/ca-test-data-manager-review-8918385)**

**Rating:** 5.0/5.0 stars

_— Deepak S._

[Read full review](https://www.g2.com/survey_responses/ca-test-data-manager-review-8918385)

**["Great tool available in market for all TDM needs"](https://www.g2.com/survey_responses/ca-test-data-manager-review-8163755)**

**Rating:** 5.0/5.0 stars

_— Verified User in Information Technology and Services_

[Read full review](https://www.g2.com/survey_responses/ca-test-data-manager-review-8163755)

#### What Are G2 Users Discussing About CA Test Data Manager?

- [What is CA Test Data Manager used for?](https://www.g2.com/discussions/what-is-ca-test-data-manager-used-for)

### [Syntheticus.ai | Synthetic Data Generator](https://www.g2.com/products/syntheticus-ai-synthetic-data-generator/reviews)

Syntheticus® is a technology company founded in 2021 and headquartered in Zürich, Switzerland. We are at the forefront of innovation and research in Privacy-Enhancing Technologies, working in collaboration with leading Swiss academic institutions. Backed by prominent investors, we are dedicated to empowering responsible business growth and promoting transparency, trust, and innovation in the data economy. Our vision centers around creating a new era of data exchange that benefits everyone. We believe in data transparency, inclusivity, and accessibility, while maintaining a strong commitment to data privacy and security. With the Syntheticus® platform, we are leading the charge in revolutionizing how businesses utilize and share data in a privacy-preserving way. The Syntheticus® platform seamlessly bridges the gap between data-driven insights and data availability, providing effortless access to high-quality synthetic datasets. Powered by cutting-edge Privacy-Enhancing Technologies, we prioritize data privacy, security, and compliance, ensuring responsible data usage. Trust in the accuracy and quality of the generated datasets with real-time validation tools and features. Safeguard sensitive information and personally identifiable data while leveraging safe, realistic alternatives to enhance privacy and mitigate compliance risks. Designed for seamless integration into sensitive work environments, our platform supports various data types, including structured tabular data, relational databases, geospatial data, time series, open text data, and more. You can also choose from Cloud, On-Premises, or EDGE infrastructure options, catering to your specific data management needs. As a proud member of the "Swiss Made Software" Label, our enterprise-ready framework is hosted on secure Google Cloud servers, providing robust data protection and reliability.

**Average Rating:** 4.3/5.0

**Total Reviews:** 11

#### Who Is the Company Behind Syntheticus.ai | Synthetic Data Generator?

- **Seller:** [Syntheticus Ltd.](https://www.g2.com/sellers/syntheticus-ltd)
- **Year Founded:** 2021
- **HQ Location:** Zurich, CH
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=dba842c06674fc5448a720b2585fa39e59fbf1ab8ac44f6f1bb3eeb2f9a84e54&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fsyntheticus%2F&secure%5Burl_type%5D=linkedin_company_website)  
4 employees on LinkedIn®

#### Who Uses This Product?

- **Company Size:** 55% Small, 36% Medium

#### What Are Recent G2 Reviews of Syntheticus.ai | Synthetic Data Generator?

**["Powerful Synthetic Data Generation for Complex Data"](https://www.g2.com/survey_responses/syntheticus-ai-synthetic-data-generator-review-12986064)**

**Rating:** 4.0/5.0 stars

_— Pratik M._

[Read full review](https://www.g2.com/survey_responses/syntheticus-ai-synthetic-data-generator-review-12986064)

**["review of Syntheticus.si"](https://www.g2.com/survey_responses/syntheticus-ai-synthetic-data-generator-review-10399688)**

**Rating:** 4.5/5.0 stars

_— preeti c._

[Read full review](https://www.g2.com/survey_responses/syntheticus-ai-synthetic-data-generator-review-10399688)

### [KopiKat](https://www.g2.com/products/kopikat/reviews)

KopiKat's Sportforma is a comprehensive dataset designed to enhance the development and evaluation of computer vision models in sports analytics. It offers a diverse collection of high-quality images and videos capturing various sports scenarios, enabling researchers and developers to train and test algorithms for tasks such as player detection, action recognition, and event classification. Key Features and Functionality: - Diverse Sports Coverage: Includes a wide range of sports, providing a broad spectrum of scenarios for model training. - High-Quality Visual Data: Offers high-resolution images and videos to ensure detailed analysis and accurate model development. - Annotated Data: Comes with comprehensive annotations, facilitating supervised learning and precise evaluation of models. - Scalable Dataset: Suitable for both small-scale experiments and large-scale model training, accommodating various research needs. Primary Value and User Solutions: Sportforma addresses the challenge of obtaining diverse and annotated sports data for computer vision applications. By providing a rich dataset, it enables users to develop robust models capable of understanding and interpreting complex sports scenes. This is particularly beneficial for applications in sports analytics, performance monitoring, and automated content generation, where accurate visual analysis is crucial.

**Average Rating:** 4.5/5.0

**Total Reviews:** 13

#### Who Is the Company Behind KopiKat?

- **Seller:** [OpenCV.ai](https://www.g2.com/sellers/opencv-ai)
- **Year Founded:** 2023
- **HQ Location:** Palo Alto, US
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=ff58a4f58fdf3fc63d14258548893843a5d8cecc3fbc40066b5a7c45f00866d1&secure%5Burl%5D=http%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fopencv-ai&secure%5Burl_type%5D=linkedin_company_website)  
13 employees on LinkedIn®

#### Who Uses This Product?

- **Company Size:** 69% Small, 23% Medium

#### What Are Recent G2 Reviews of KopiKat?

**["A great tool for ideas"](https://www.g2.com/survey_responses/kopikat-review-9941880)**

**Rating:** 5.0/5.0 stars

_— Rafael Henrique R._

[Read full review](https://www.g2.com/survey_responses/kopikat-review-9941880)

**["When every detail matters, KopiKat delivers."](https://www.g2.com/survey_responses/kopikat-review-11389319)**

**Rating:** 5.0/5.0 stars

_— Verified User in Marketing and Advertising_

[Read full review](https://www.g2.com/survey_responses/kopikat-review-11389319)

### [Synthesis AI](https://www.g2.com/products/synthesis-ai/reviews)

Synthesis AI is a pioneering synthetic data technology which builds more capable AI

**Average Rating:** 4.2/5.0

**Total Reviews:** 11

#### Who Is the Company Behind Synthesis AI?

- **Seller:** [Synthesis](https://www.g2.com/sellers/synthesis-863e5e7a-d8da-42fd-a274-f85882c524af)
- **Year Founded:** 2019
- **HQ Location:** San Francisco, CA
- **Twitter:** @SynthesisAI\_  
645 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=2287850d60bd5d412d493d57000841b7cbf361e412e31b8cce209858549cb1ed&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fsynthesis-ai&secure%5Burl_type%5D=linkedin_company_website)  
15 employees on LinkedIn®

#### Who Uses This Product?

- **Company Size:** 73% Small, 27% Medium

#### What Are Recent G2 Reviews of Synthesis AI?

**["Best AL Educational Content"](https://www.g2.com/survey_responses/synthesis-ai-review-9938816)**

**Rating:** 5.0/5.0 stars

_— Shanna B._

[Read full review](https://www.g2.com/survey_responses/synthesis-ai-review-9938816)

**["My Honest Review for Synthesis AI"](https://www.g2.com/survey_responses/synthesis-ai-review-9949066)**

**Rating:** 4.0/5.0 stars

_— Saurabh B._

[Read full review](https://www.g2.com/survey_responses/synthesis-ai-review-9949066)

### [MOSTLY AI Synthetic Data Platform](https://www.g2.com/products/mostly-ai-synthetic-data-platform/reviews)

The MOSTLY AI synthetic data platform is the leading synthetic data generator globally. Its platform enables enterprises across industries to unlock, share, fix and simulate data. Thanks to the advances in artificial intelligence ,MOSTLY AI's synthetic data look and feel just like real data, are able to retain the valuable, granular-level information, yet guarantee that no individual is ever getting exposed. This enables businesses to drive innovation and digital transformation, overcome data silos, improve machine learning models as well as application testing capabilities. MOSTLY AI serves customers in a variety of verticals, including banking, insurance and telecommunications.

**Average Rating:** 4.5/5.0

**Total Reviews:** 17

#### Who Is the Company Behind MOSTLY AI Synthetic Data Platform?

- **Seller:** [MOSTLY AI](https://www.g2.com/sellers/mostly-ai)
- **Year Founded:** 2017
- **HQ Location:** Vienna, Wien
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=769bd670df1e2de370c1dae482918c887d856ad92d7cdc9c00cc69e58c258779&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fmostlyai%2F&secure%5Burl_type%5D=linkedin_company_website)  
41 employees on LinkedIn®

#### Who Uses This Product?

- **Company Size:** 53% Small, 24% Medium

#### What Are Recent G2 Reviews of MOSTLY AI Synthetic Data Platform?

**["Great synthetic data in a timely fashion"](https://www.g2.com/survey_responses/mostly-ai-synthetic-data-platform-review-8829318)**

**Rating:** 5.0/5.0 stars

_— Rohit K._

[Read full review](https://www.g2.com/survey_responses/mostly-ai-synthetic-data-platform-review-8829318)

**["A simple and straightforward tool to synthesize data"](https://www.g2.com/survey_responses/mostly-ai-synthetic-data-platform-review-9151912)**

**Rating:** 5.0/5.0 stars

_— Quang B._

[Read full review](https://www.g2.com/survey_responses/mostly-ai-synthetic-data-platform-review-9151912)

### [Syntho](https://www.g2.com/products/syntho/reviews)

Syntho is an Amsterdam-based company revolutionizing the tech industry with AI-generated synthetic data. As the leading provider of synthetic data software, Syntho’s mission is to empower businesses worldwide to generate and leverage high-quality Synthetic Data at scale. Syntho solves 3 main data access problems: 1. 𝗔𝗜-𝗴𝗲𝗻𝗲𝗿𝗮𝘁𝗲𝗱 𝗱𝗮𝘁𝗮 𝗳𝗼𝗿 𝗮𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀: Mimic the statistical patterns, relationships, and characteristics of original data in synthetic data with the power of artificial intelligence (AI) algorithms. Clients may share synthetic data and use it for AI modeling. 2. 𝗦𝗺𝗮𝗿𝘁 𝗱𝗲-𝗶𝗱𝗲𝗻𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻: De-identification is a process used to protect sensitive information by removing or modifying personally identifiable information (PII) from a dataset or database. 3. 𝗧𝗲𝘀𝘁 𝗱𝗮𝘁𝗮 𝗺𝗮𝗻𝗮𝗴𝗲𝗺𝗲𝗻𝘁: Leverage synthetic data in a robust solution for ensuring data privacy, accuracy, and utility in testing environments. By generating realistic synthetic datasets, enables comprehensive testing while safeguarding sensitive information, accelerating development cycles, and optimizing resource allocation.

**Average Rating:** 4.6/5.0

**Total Reviews:** 16

#### Who Is the Company Behind Syntho?

- **Seller:** [Syntho](https://www.g2.com/sellers/syntho)
- **Year Founded:** 2020
- **HQ Location:** Amsterdam, Noord Holland
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=6bafe3ca727aa0e965d59ffb1fc4c42ed69645cff9a9c165bba3e4370e813d0d&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fsyntho%2F&secure%5Burl_type%5D=linkedin_company_website)  
11 employees on LinkedIn®

#### Who Uses This Product?

- **Company Size:** 69% Small, 19% Medium

#### What Are Recent G2 Reviews of Syntho?

**["Generating synthetic data has never been easier"](https://www.g2.com/survey_responses/syntho-review-8274442)**

**Rating:** 4.5/5.0 stars

_— Punit S._

[Read full review](https://www.g2.com/survey_responses/syntho-review-8274442)

**["Syntho AI - Great Tool"](https://www.g2.com/survey_responses/syntho-review-8284309)**

**Rating:** 4.0/5.0 stars

_— Verified User in Computer & Network Security_

[Read full review](https://www.g2.com/survey_responses/syntho-review-8284309)

### [GenRocket](https://www.g2.com/products/genrocket/reviews)

GenRocket is the technology leader in synthetic data generation for quality engineering and machine learning use cases. We call it Synthetic Test Data Automation (TDA) and it's the next generation of Test Data Management (TDM). GenRocket provides a comprehensive self-service platform to more than 50 of the world's largest organizations who demand superior quality and efficiency in their quality engineering and data science operations. KEY FEATURES SPEED: Data generated at 10,000 rows/second and one billion rows in under two hours QUALITY: Any volume and variety of data (unique, negative, conditioned, permutations) REUSABILITY: Test Data Cases and Test Data Rules can be easily reused SELF-SERVICE: Model, design and deploy test data on-demand into CI/CD Pipelines SECURITY: Secure platform never uses or stores sensitive customer data VERSATILITY: 101+ data formats e.g. SQL, XML, JSON, EDI, PDF, Kafka, Parquet, AWS S3 VALUE FOR MONEY: Attractive license and implementation cost to maximizes value PROVEN BENEFITS ACCELERATION: 100 times faster than creating data in spreadsheets or via scripts COVERAGE: Improve test coverage from less than 50% to more than 90% to maximize quality VALUE: Reduce TCO by 90% when compared to traditional Test Data Management

**Average Rating:** 4.6/5.0

**Total Reviews:** 9

#### Who Is the Company Behind GenRocket?

- **Seller:** [GenRocket](https://www.g2.com/sellers/genrocket)
- **Year Founded:** 2012
- **HQ Location:** Ojai, CA
- **Twitter:** @GenRocketINC  
370 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=31a8d3883a9552f930fd6f701de7a0d6ff542d11561c60fceb37e59e0f8ba054&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fgenrocket&secure%5Burl_type%5D=linkedin_company_website)  
33 employees on LinkedIn®

#### Who Uses This Product?

- **Company Size:** 73% Large, 27% Small

#### What Are Recent G2 Reviews of GenRocket?

**["Genrocket is one of the best synthetic data generator tool"](https://www.g2.com/survey_responses/genrocket-review-5268840)**

**Rating:** 4.5/5.0 stars

_— Mohammad H._

[Read full review](https://www.g2.com/survey_responses/genrocket-review-5268840)

**["Comprehensive database management software"](https://www.g2.com/survey_responses/genrocket-review-6614732)**

**Rating:** 5.0/5.0 stars

_— Nineta U._

[Read full review](https://www.g2.com/survey_responses/genrocket-review-6614732)

#### What Are G2 Users Discussing About GenRocket?

- [What is test data management tool?](https://www.g2.com/discussions/what-is-test-data-management-tool)
- [Why we need test data generation in software testing?](https://www.g2.com/discussions/why-we-need-test-data-generation-in-software-testing) - 1 comment
- [How does GenRocket generate data?](https://www.g2.com/discussions/how-does-genrocket-generate-data) - 1 comment
- [What does GenRocket do?](https://www.g2.com/discussions/what-does-genrocket-do) - 1 comment

### [Marvin AI](https://www.g2.com/products/marvin-ai/reviews)

Marvin processes structured data for software development, enhancing your software development process.

**Average Rating:** 4.3/5.0

**Total Reviews:** 12

#### Who Is the Company Behind Marvin AI?

- **Seller:** [Askmarvinai](https://www.g2.com/sellers/askmarvinai)
- **HQ Location:** N/A
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=7886df2ed926834e5eb248c77dcfa8e5c815d3ab1f0fe3132ced0dba45868834&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2FNo-Linkedin-Presence-Added-Intentionally-By-DataOps&secure%5Burl_type%5D=linkedin_company_website)  
1 employees on LinkedIn®

#### Who Uses This Product?

- **Company Size:** 50% Small, 33% Medium

#### What Do G2 Reviewers Say About Marvin AI?

_AI-generated summary from verified user reviews_

##### Pros

- Users find Marvin AI's **ease of use** impressive, appreciating its simple and straightforward integration process.
- Users appreciate the **simplicity and versatility** of Marvin AI, enabling faster app development and smarter decision-making.
- Users appreciate the **lightweight and scalable AI functionalities** of Marvin AI, enhancing their decision-making with ease.
- Users appreciate the **easy integrations** of Marvin AI, facilitating a smooth implementation with GitHub and scalability.
- Users praise Marvin AI for its **efficiency in app development** , delivering fast and optimized results effortlessly.

##### Cons

- Users note the **limited community support** for Marvin AI, which can hinder its effectiveness for smaller projects.
- Users note the **limited community support** for Marvin AI, which may hinder assistance and resources for projects.
- Users note **usage limitations** due to less community support and data requirements impacting performance in smaller projects.
- Users find the **complex implementation** process of Marvin AI frustrating due to repeated installation attempts via Git.
- Users find the **complex setup** of Marvin AI frustrating, often needing repeated installations via Git.

#### What Are Recent G2 Reviews of Marvin AI?

**["Reduced complexities for building AI from scratch"](https://www.g2.com/survey_responses/marvin-ai-review-10223112)**

**Rating:** 4.0/5.0 stars

_— Tejas S._

[Read full review](https://www.g2.com/survey_responses/marvin-ai-review-10223112)

**["Best to Integrate AI in your Python project"](https://www.g2.com/survey_responses/marvin-ai-review-10198628)**

**Rating:** 5.0/5.0 stars

_— Gaurav S._

[Read full review](https://www.g2.com/survey_responses/marvin-ai-review-10198628)

### [AI vision](https://www.g2.com/products/ai-vision/reviews)

Deep Vision Data specializes in the creation of synthetic training data for supervised and unsupervised training of machine learning systems such as deep neural networks, and also the development of XR environments as reinforcement and imitation learning platforms.

**Average Rating:** 4.1/5.0

**Total Reviews:** 7

#### Who Is the Company Behind AI vision?

- **Seller:** [Deep Vision Data](https://www.g2.com/sellers/deep-vision-data)
- **HQ Location:** N/A
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=7886df2ed926834e5eb248c77dcfa8e5c815d3ab1f0fe3132ced0dba45868834&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2FNo-Linkedin-Presence-Added-Intentionally-By-DataOps&secure%5Burl_type%5D=linkedin_company_website)  
1 employees on LinkedIn®

#### Who Uses This Product?

- **Company Size:** 38% Small, 38% Medium

#### What Are Recent G2 Reviews of AI vision?

**["A very complete solution"](https://www.g2.com/survey_responses/ai-vision-review-10028344)**

**Rating:** 4.5/5.0 stars

_— Emily C._

[Read full review](https://www.g2.com/survey_responses/ai-vision-review-10028344)

**["Improve the model training process"](https://www.g2.com/survey_responses/ai-vision-review-10419154)**

**Rating:** 5.0/5.0 stars

_— Jacek F._

[Read full review](https://www.g2.com/survey_responses/ai-vision-review-10419154)

### [K2View](https://www.g2.com/products/k2view/reviews)

K2view Data Product Platform composes and delivers operational context as reusable data products to power use cases such as agentic AI, Customer 360, synthetic data generatio, data privacy and compliance, and test data management. Operational context represents complete, governed, real-time views of business entities such as customers, orders, and products, enabling consistent, trusted data for operational, analytical, and AI use cases. The platform integrates fragmented data from multiple sources into consistent, continuously updated data products, delivered on demand to downstream systems and users. Each data product is a self-contained unit that integrates and organizes multi-source data by entity, persists it in a high-performance Micro-Database, and governs it in-flight. It processes and enriches data in memory, continuously synchronizes it with source systems, and delivers it to authorized systems via APIs, SQL, messaging, CDC, MCP, and RAG. Core capabilities include: • K2Studio: Graphical tool for designing, creating, and deploying data products, accelerated by AI copilots • Universal Connectivity & Integration: Connect to any source or target (structured, semi-structured, unstructured) across cloud and on-prem, supporting batch and real-time, sync/async, and push/pull delivery • Augmented Data Catalog and Governance: AI-driven discovery and classification with in-flight enforcement of data privacy and data quality policies • Advanced Transformation: In-memory (RAM) data transformations and enrichment for near-real-time processing • AI & Agentic Enablement: Built-in MCP server per data product and ability to create data agents with planning, reasoning, and execution capabilities • Flexible Deployment: Cloud, on-prem, hybrid; supports fabric, mesh, hub architectures • K2Cloud Monitoring: Visibility into data product usage and SLAs

**Average Rating:** 4.6/5.0

**Total Reviews:** 52

#### Who Is the Company Behind K2View?

- **Seller:** [K2View](https://www.g2.com/sellers/k2view)
- **Year Founded:** 2009
- **HQ Location:** Dallas, TX
- **Twitter:** @K2View  
142 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=baf2cbdbb70d0e5346130463845539d6aecc39aef46a177b586eb301cf96104f&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F1012853&secure%5Burl_type%5D=linkedin_company_website)  
194 employees on LinkedIn®

#### Who Uses This Product?

- **Top Industries:** Telecommunications, Information Technology and Services
- **Company Size:** 42% Large, 31% Small

#### What Do G2 Reviewers Say About K2View?

_AI-generated summary from verified user reviews_

##### Pros

- Users value the **efficient data management** capabilities of K2View, enhancing data organization and compliance across multiple systems.
- Users value the **seamless data sharing** of K2View, enhancing efficiency and simplifying access to compliant data.
- Users appreciate the **ease of use** of K2View, simplifying data access and management across multiple systems.
- Users value the **efficiency** of K2View, streamlining data management and reducing delays across multiple systems.
- Users appreciate the **efficient organization of data** , allowing seamless access and management across various systems.

##### Cons

- Users find K2View's **complexity** challenging, especially during setup and optimization, requiring a solid technical background.
- Users find the **complex setup** of K2View challenging, especially lacking necessary technical expertise for efficient use.
- Users find the **high technical requirement** of K2View challenging, complicating configuration and maintenance without adequate expertise.
- Users face a **steep learning curve** with K2View due to complex setup and a lack of practical training resources.
- Users find K2View's **learning difficulty** challenging, especially in configuration and understanding advanced features without technical expertise.

#### What Are Recent G2 Reviews of K2View?

**["A Dependable Platform for Managing Complex Enterprise Data"](https://www.g2.com/survey_responses/k2view-review-13125513)**

**Rating:** 5.0/5.0 stars

_— Mario C._

[Read full review](https://www.g2.com/survey_responses/k2view-review-13125513)

**["Improving Confidence in Data Quality and Governance"](https://www.g2.com/survey_responses/k2view-review-13112374)**

**Rating:** 5.0/5.0 stars

_— Meerte V._

[Read full review](https://www.g2.com/survey_responses/k2view-review-13112374)

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 ![Bijou Barry](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Bijou Barry")
BB

Researched and written by [Bijou Barry](https://research.g2.com/insights/author/bijou-barry)

Updated April 9, 2026

Synthetic data software generates artificial datasets, including images, text, and structured data, based on original data, preserving the mathematical characteristics and statistical relationships of the source while protecting privacy-sensitive information, enabling data scientists and ML engineers to build datasets for testing, model training, and simulation.

### Core Capabilities of Synthetic Data Software

To qualify for inclusion in the Synthetic Data category, a product must:

- Generate synthetic data such as images and structured data
- Convert privacy-sensitive data into a fully anonymous dataset while maintaining granularity
- Work out of the box, ensuring the generative model can automatically generate data without being explicitly programmed to do so

### Common Use Cases for Synthetic Data Software

Data scientists, ML engineers, and researchers use synthetic data platforms to overcome data shortages and privacy constraints in AI development. Common use cases include:

- Generating training datasets for [machine learning](https://www.g2.com/categories/machine-learning) models when real-world data is scarce, sensitive, or unavailable
- Testing and validating algorithms in simulated environments that replicate real-world conditions
- Reducing algorithmic bias by supplementing or rebalancing original datasets with synthetic examples

### How Synthetic Data Software Differs from Other Tools

Synthetic data software differs from [data masking software](https://www.g2.com/categories/data-masking), which protects private information by obscuring existing data but does not generate artificial datasets or support large-scale dataset creation. Synthetic data platforms can create entirely new data from scratch using methods such as generative neural networks ([GAN](https://www.g2.com/glossary/gan-definition)s) and CGI, enabling broader use cases in model training and simulation that data masking cannot address. Some synthetic data tools also relate to the [synthetic media](https://www.g2.com/categories/synthetic-media) category but are specifically focused on structured and unstructured datasets rather than media production.

### Insights from G2 on Synthetic Data Software

Based on category trends on G2, data privacy compliance and the ability to generate realistic training datasets at scale stand out as standout capabilities. Accelerated model development timelines and reduced dependency on sensitive real-world data stand out as primary outcomes of adoption.

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