Generate high-quality and compliant data samples at scale, built with GenAI.
To drive growth, product development, and innovation, you need easy and secure access to large volumes of data. But getting real-world data is often complex, storing and managing it is costly, and using it comes with privacy and bias concerns and regulatory restrictions.
GenAI-powered synthetic data offers an artificial alternative to real-world data. It serves as a secure, anonymous, and statistically representative solution, addressing all the challenges related to access, bias, storage, and compliance commonly associated with real-world data.
AI and LLM are in constant need of more training data, creating tension between the desire for data and the limitations imposed by data privacy regulations.
While there's an ongoing demand for high-quality datasets, the truth is that real-world data is at maximum capacity. We’ve already scraped the entire internet, and we’re left with limited access to additional valuable information.
Synthetic data unlocks the full potential of AI and ML projects by providing diverse and high-quality datasets, enhancing data fairness, ensuring legal compliance, and boosting AI and LLM performance.
Synthetic data empowers organizations to streamline software testing processes, overcome data limitations, and ensure seamless end-to-end testing for more efficient software development.
Synthetic data enables analytics and business intelligence operations across cloud, on-premises, and edge environments by removing data access, regulatory compliance, and cloud computing challenges.
Engineered to bridge the gap between data availability and actionable insights, the Syntheticus Suite integrates a Core Platform with a set of advanced Functional Modules to supercharge innovative applications. Together, they form the ecosystem of Syntheticus.ai, empowering your data-driven initiatives.
By 2025, synthetic data will reduce personal customer data collection, avoiding 70% of privacy violation sanctions.
According to Forbes, research shows that 79% of consumers are concerned about data security and privacy issues, especially as the number and severity of data breaches increases.
Through 2030, for data used to train AI models, synthetic structured data will grow at least 3x as fast as real structured data.
IDC research shows that by 2025 the amount of data created globally will grow fivefold and reach 175 zettabytes (175 trillion GB) to be compared with 33ZB in 2018.
By 2030, for unstructured data, synthetic data will constitute >95% of data used for training AI models.
Synthetic data is a technical solution to a legal problem.
Stay up to date with the latest blog posts and news from Syntheticus®
Sign up for a free demo, see Syntheticus® in action, and start leveraging the benefits of high-quality synthetic data.