Dedomena brings the fastest, most effective and highest ROI approach to enterprise AI by combining pre-built AI solutions with embedded synthetic data and anonymization capabilities. Train, deploy and monitor best-in-class machine learning models, and unlock the value of your data.
Test and fine-tune your models with embedded privacy-preserving synthetic data capabilities.
Train your models with large synthetic copies of your data and monitor performance by incorporating feedback from systems and users.
We have already built and tested the models you need, you just have to integrate them or fine-tune them with synthetic copies of your data.
Deploy and scale a tested AI application through our API and deliver real-time insights into your system, users and customers.
Our mission is to accelerate the development and adoption of Artificial Intelligence
Browse AI applets based on your business needs, goals and expected outcome.
Test and safely fine-tune your models with tons of synthetic copies of your original data.
Easily integrate your trained model into production environments and start delivering great value to your customers.
Monitor accuracy and incorporate feedback into the model for an incredible performance.
Accelerate delivery and reduce the complexities of developing Artificial Intelligence.
Use pre-built AI applications and streamline your data operations with industry-specific frameworks.
Rapidly deploy AI applications and capabilities in days and see results in weeks rather than months or even years.
Extract the value of your data and take a competitive advantage from reduced costs and increased revenue.
Ensure data privacy with embedded anonymization and synthetic data generation capabilities.
Businesses of every size can now take advantage of implementing Artificial Intelligence from a fraction of the cost.
Encourage developers and experts to create, innovate, and become actively involved in organisational strategy thanks to its flexibility and ease of use.
Dedomena AI technology has been designed to improve AI performance across industries and purposes.
Evaluate customers based on financial behaviour.
Pinpoint fraud risks for timely action to prevent revenue loss and fraud-related costs.
Understand customer´s transactionability with purchase and income categories, and merchant information.
Pre-qualify low-risk candidates using AI models and expedite their approvals.
Transform financial crime detection with AI.
Accurately forecast revenue, balances with AI that identifies risks and opportunities.
Extract data from electronic health records (EHRs) and automatically turn it into usable, computer-addressable information.
Machine-learning-based disease diagnosis for predictive and effective treatment.
Extract clinical concepts from electronic health records into actionable knowledge.
Enable underlying exchange and sharing of clinical information in industry standards.
Structure patient records making research reliable, reproducible and efficient.
Check out some of our explanatory articles or cross-industry
use cases to know more
Synthetic Data can help insurance companies to improve their underwritting, claims management and customer experience while unlocking the potential of data that have been hidden by data privacy regulations.
5 min read
Companies now have access to more employee data than ever before, and, as data collection becomes easier, it is more important than ever for HR to take position on ethical data use, privacy and security.
4 min read
Synthetic data has received considerable attention as a method of protecting patient privacy, diversifying datasets and augmenting clinical research, hence accelerating the application of Artificial Intelligence across different hospitals and institutions.
3 min read
Data anonymization is key to applying the best data-driven strategies in the banking industry. The correct implementation of this strategy based on synthetic data will allow extracting all the knowledge and insights from customer financial data.
5 min read
The banking industry faces a wide variety of challenges when it comes to anonymization and data privacy. Thanks to synthetic data, banks can tackle data challenges more effectively and unlock the full potential of their data assets.
3 min read
The techniques that have always been used to anonymize data do not have the guarantee of ensuring the total anonymity of the data. These are techniques that have flaws when it comes to ensuring data privacy and utility.
4 min read