Besides preserving the statistical properties of the original data, our methods preserve the data quality and structure, ensuring high-quality data for purposes such as training ML models.
Dedomena is the platform that helps companies develop scalable AI solutions by putting data at the heart of their strategy
We provide an user interface and/or API for companies to easily create synthetic data projects and integrate synthetic data into existing data pipelines and processes.
Generating data that looks real sounds like a fantastic playground for your business.
Reducing time-to-data and time-to-market from months to days. Up to 50X shorter time-to-data.
Accessing fully anonymous synthetic behavioural data. 90% more data for your customer data analytics projects
Work with larger volumes of synthetic data that retains structure, patterns and value. Improve ML performance by 20-40%.
Minimizing the need of processing real customer data. $3.5 million is the average cost to remediate a data breach.
Say goodbye to data compliance bureaucracy and endlerr processes. Reduce data provisionning costs by 75%.
Share synthetic versions of your customer data. Reduce up to 80% on data delivery time and costs
Developing successful data-centric initiatives requires access to large amounts of high-quality and secure data.
Improved Machine Learning
In AI and ML development, synthetic data is better than real data. Synthetic data can also be augmented and create records to fix biases.
Take your data monetization strategy further by selling packages of synthetic data to third parties.
Even though the original data is no longer in the custody of the entity, there is no limit on how long or for what purpose the synthetically generated data can be used.
Testing & Development
Synthetic data empower engineers to create and test software applications in shorter development cycles, making products come to life before launching.
Vendor evaluation and Hackathons
Oursource innovation, design, development and testing of data-intensive applications eliminating the lag in the process.
Synthetic data function as production data but anonymous, so that it can be used and shared with partners and providers for PoCs, software testing and advanced analytics projects.
Check out some of our explanatory articles or cross-industry
use cases to know more