

Syntheticus empowers data exchange and overcomes limitations in data access, scarcity, and bias - at scale. With our synthetic data platform, you generate high-quality and compliant data samples tailored to your business needs and analytics goals.
You need easy and secure access to data to drive growth, product development, and innovation. However, production data is either not accessible or not really usable, making it difficult to gain the insights you need.
That's where synthetic data comes in.
With synthetic data, you easily tap into a wide range of high-quality sources that are not always available in the real world.
By accessing high-quality, consistent data, you conduct more reliable research, leading to better products, services, and business decisions.
With fast, reliable data sources at your fingertips, you accelerate product development cycles and improve time-to-market.
Synthetic data is designed to be private and secure by default, protecting sensitive data and maintaining compliance with privacy laws and regulations.
Use synthetic data to generate mock data for experimentation and validation. It allows you to evaluate software, systems, products, and services without compromising the privacy and security of sensitive data.
With synthetic data, you enrich existing datasets by identifying patterns and trends. Enriched datasets are used to detect and flag anomalous behavior, uncover hidden correlations, and generate targeted insights.
With fast and reliable data sources, you run predictive analytics to understand customer behavior better, anticipate market trends, and optimize operations. Use synthetic data to train Machine Learning models for more accurate predictions and recommendations.
With synthetic data, you don't have to worry about exposing sensitive data to unauthorized users. Share and collaborate on datasets with stakeholders across departments and teams without risking the privacy or integrity of your data.
Whether working with large, original datasets or smaller, more focused datasets, synthetic data augments your existing data to produce higher-quality insights. Use it to fill gaps, build more representative models, or test and validate findings and assumptions.
Syntheticus enables insurance companies to tap into a wide range of high-quality data sources, improving risk assessment and forecasting to minimize potential losses.
With access to synthetic data, financial institutions run predictive analytics and detect anomalies, optimizing operations and minimizing risks.
Syntheticus allows healthcare providers and pharma companies to accelerate research and development, enhancing privacy and security while maintaining compliance with industry regulations.
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.
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