YData
YData helps data-science teams access, understand, manage and improve data so they can build better AI. Its products combine data profiling, synthetic-data generation and data-preparation workflows, with privacy and responsible AI at the center.
At a Glance
- Data-science and machine-learning teams
- Enterprise AI developers
- Financial services
- Utilities and energy
- +5 more
AI Tools by YData
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YData
Data Profiling and Synthetic Data
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Latest News
KPMG announced an agreement to acquire YData Labs Inc.’s IP and technology assets, including its platform and SDK, and establish a Synthetic Data Center of Excellence.
YData announced synthetic Q&A/prompt-response and synthetic document generation for PDF, DOCX and HTML in its SDK.
YData announced that it achieved the top statistical-accuracy ranking in AIMultiple’s 2025 synthetic-data benchmark.
YData published an IGLOO case study describing synthetic-data use for cybersecurity, reporting 98.8% precision and 99% true positives.
Products & Services
A data-development platform for structured data combining a data catalog, automated profiling, synthetic data, collaborative Labs and scalable data-preparation pipelines. It is available as cloud/self-hosted software, including AWS and Azure Marketplace deployment, and can run on-premises on Kubernetes.
A Python toolkit for privacy-first AI and agentic-AI development, covering connectors, metadata, data profiling, synthetic data and anonymization. It supports tabular, time-series, relational, text and document data and multiple LLM backends.
An open-source, one-line exploratory-data-analysis and data-quality profiling package that produces HTML, JSON and notebook reports, with type inference, warnings, univariate and multivariate analysis, time-series and text analysis, dataset comparison and Spark support. The supplied repository now states that the package has been renamed to fg-data-profiling.
Generators for tabular, time-series, multi-table/relational, text, Q&A and document data, designed to preserve statistical and structural properties without reproducing individual records.
Market Position
YData positioned itself as a data-centric AI platform that combines profiling, data quality, synthetic data and workflow orchestration rather than offering only a standalone generator or profiler. Its 2025 YData-published summary of AIMultiple’s benchmark reported that YData was the most statistically accurate of seven publicly available generators, comparing it with Mostly AI, Gretel and Synthetic Data Vault (SDV).
Leadership
Founders
Gonçalo Martins Ribeiro
Data-science leader who had been managing data-science teams before co-founding YData; he became Co-Founder and CEO and led the company’s US expansion.
Fabiana Clemente
Lead data scientist before co-founding YData; she became Co-Founder and Chief Data Officer. Her academic background includes a B.Sc. in Applied Mathematics from the University of Lisbon and an M.Sc. in Applied Econometrics and Forecasting.
Executive Team
Gonçalo Martins Ribeiro
Co-Founder and CEO
Previously managed data-science teams; led YData’s strategy and US expansion. KPMG said he was expected to join KPMG in connection with its 2025 transaction.
Fabiana Clemente
Co-Founder and Chief Data Officer
Previously a lead data scientist; holds a B.Sc. in Applied Mathematics and an M.Sc. in Applied Econometrics and Forecasting. KPMG said she was expected to join KPMG in connection with its 2025 transaction.
Founding Story
The founders had experienced the data-quality problem from both management and technical perspectives. They interviewed more than 100 data scientists and found broad agreement that access to high-quality data was a primary obstacle; YData was started to make data preparation, quality assessment and improvement easier before model training.
Business Model
Revenue Model
Freemium and usage-based software: a free/community tier, pay-as-you-go credits for profiling and synthetic-data generation, plus enterprise subscriptions with predictable pricing, additional security/control/support and private-cloud or on-premises deployment.
Pricing Tiers
All features, 20+ connectors, automated profiling, comparison reports, synthetic data generation and synthetic database generation.
1 credit per 1 million data points or 10,000 tokens; credits cover profiling, synthetic data, Q&A-pair and synthetic-document generation; minimum transaction 0.1 credits.
All features with predictable pricing and enterprise scalability, security, control and support.
20+ connectors, Data Catalog, automated profiling, Labs, synthetic data generation and Fabric SDK.
Adds automated database profiling, enhanced Labs, synthetic database generation, pipelines, unlimited scalability, concurrent users and self-hosting on AWS/Azure.
Adds predictable pricing and private-cloud or on-premises deployment.
Target Markets
- Data-science and machine-learning teams
- Enterprise AI developers
- Financial services
- Utilities and energy
- Telecommunications
- Healthcare
- Exploratory data analysis and data-quality validation
- Preparing and improving training data for machine-learning models
- Generating privacy-safe data for regulated sharing and collaboration
- Augmenting imbalanced or scarce datasets
- Synthetic database and transaction-data generation
- LLM fine-tuning, RAG evaluation and agent benchmarking
- IGLOO Corporation
- Revolut
- EDP Distribuição