This company provides accelerated computing platforms and software solutions for AI, high-performance computing, and data centers. They offer specialized hardware like GPUs and integrated systems to power demanding workloads across various industries. Their technology enables advancements in areas ranging from autonomous vehicles and robotics to scientific visualization and generative AI development.
Funding
$67.7M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Organizations struggle to leverage data for AI model training and validation due to privacy concerns and limited access to high-quality datasets. Traditional anonymization techniques can degrade data utility, hindering the development of accurate and reliable AI models.
Solution
Gretel provides a multimodal synthetic data platform that uses generative AI and privacy-enhancing technologies to create artificial datasets that mirror the statistical properties of real data. The platform's APIs enable developers to generate anonymized and safe synthetic data on demand, improving AI models without compromising privacy. Gretel allows users to train generative AI models, validate models with quality and privacy scores, and generate large volumes of data when needed. The platform supports various deployment options, including cloud-based and on-premise environments, ensuring data remains secure and compliant with privacy regulations.
Target Audience
Gretel's primary customers are data scientists, machine learning engineers, and AI developers in enterprises and research institutions who need access to high-quality, privacy-safe data for AI model development and validation.
Features
- Generative AI models that learn the statistical properties of real data
- Quality and privacy scoring to validate synthetic data utility and safety
- Support for multimodal data types, including structured, unstructured, and time-series data
- Cloud-based and on-premise deployment options for flexible data governance
- APIs for programmatic synthetic data generation and integration with existing workflows
- Gretel Navigator Data Designer for visual data exploration and synthetic data configuration
- Integration with Amazon AWS, Databricks, Google GCP, and Microsoft Azure