The Infrastructure for the Data & AI Economy
Dedomena.AI is the enterprise platform that turns data into trusted digital assets and business value, unlocking AI. Connect. Analyze. Validate. Protect. Generate. Predict. Collaborate. Monetize. Bring together data readiness, privacy-preserving technologies, AI models, intelligent agents, secure collaboration and lifecycle governance in one interoperable platform, while maintaining control over your data. Secure. Governed. Scalable. By design.
Data Validation
Get reliable data through automated profiling, cleaning and validation. Identify quality issues, sensitive information, bias and regulatory risks before they affect downstream use.
Anonymization
Protect sensitive information and enable responsible data use through advanced anonymization, and privacy-preserving techniques.
Synthetic Data
Generate high-fidelity synthetic datasets for analytics, testing, AI development and secure data collaboration, reducing reliance on original sensitive records.
Neurons
Plug & play or build intelligent applications and agents that enrich data, analyze, process, infer and support complex operational processes using governed data and AI capabilities.
Data Space
Enable secure data sharing and federated collaboration across organizations while maintaining control over data access and creating opportunities for interoperability, licensing and monetization.
Trusted by the best
Dedomena enables data-driven companies to accelerate the use of their information without restrictions, ensuring privacy and quality.
Why choose Dedomena?
Turn fragmented enterprise data into trusted, usable assets for analytics, experimentation and AI development.
Prepare and validate data for downstream use.
Reduce project and proof-of-concept timelines by up to 85%.
Enable experimentation and knowledge sharing through data innovation initiatives and hackathons.
Related articles
Check out some of our explanatory articles or cross-industry use cases to know more.
AI Transparency Is Entering a New Phase in Europe: From Disclosure to Demonstrable Transparency
AI transparency is entering a new phase in Europe. With Article 50 of the EU AI Act now applying, organizations need to move beyond simply disclosing AI use and start embedding transparency directly into their systems, content and workflows.
From Governance Documents to Policy-as-Code: Why Financial AI Needs Executable Governance
Traditional governance documents are no longer enough for enterprise AI.
Building an AI Credit Scoring System Under the European AI Act: What We Learned from OpenScore
Financial institutions can now estimate default probabilities with a level of precision that was difficult to imagine only 10 to 15 years ago
Data Segmentation in the Age of AI: From Organization to Activation
Data segmentation has evolved further towards
Redefining Cybersecurity in the Age of AI
Cybersecurity is shifting from protecting systems to protecting data. Learn how organizations can unlock AI safely using synthetic data, secure data spaces, and compliance-by-design frameworks.
Data Outliers, biasses and noises: Invisible Risks
In the development of AI solutions, three invisible threats compromise model quality, precision, and fairness: outliers, bias, and noise.
