Real data, protected identities.
Personal data is automatically discovered and masked, preserving referential integrity and statistical value for training.
Perforce Delphix for artificial intelligence
AI-ready data, compliant by design.
With Perforce Delphix we give data science, analytics and development teams realistic, masked or synthetic data to train, test and validate models and agents without exposing sensitive information.
The challenge
AI is hungry for data. Compliance isn't.
Models, agents and analytics perform best on realistic, up-to-date data. But copying production data into data lakes, pipelines and development environments multiplies privacy risk, storage costs and compliance headaches.
Delphix solves the problem at the root: sensitive data is discovered and masked before it leaves production, and every team gets the data it needs in self-service, already compliant.
Our approach
Trustworthy data for every stage of the AI lifecycle.
The scenarios you don't have yet.
Generated data for new features, edge cases and testing of AI-based applications and agents.
Always fresh, never duplicated.
Virtual copies you can refresh, rewind and version in minutes: repeatable experiments without multiplying storage.
Centralized governance and audit.
Policies, access and traceability across all non-production environments, supporting GDPR, DORA and the AI Act.
Areas of application
Where Delphix makes the difference in AI projects.
Concrete use cases, to pick based on your data and your goals.
Model training and fine-tuning
Realistic datasets with masked personal data, to train and specialize models without taking sensitive information out of production.
- Data masking
- ML
- LLM
Testing AI applications and agents
Synthetic data to cover edge cases and new scenarios, and test environments that reset in minutes between cycles.
- Synthetic data
- Test automation
- Agents
Compliant analytics and data lakes
Data masking in data warehouses, data lakes and ETL pipelines, for analysis and reporting without exposing identities or confidential data.
- Data warehouse
- Data lake
- ETL
On-demand environments for data science
Virtual databases created in self-service for every experiment, refreshed from production and already masked, with no waiting and no physical copies.
- Data virtualization
- Self-service
- API
Validation and reproducibility
Rewind and version data to compare models on the same datasets, rerun tests and rebuild the exact conditions behind a result.
- Rewind
- Versioning
- MLOps
Compliance for AI
Centralized policies and traceability of the data used by models and agents, supporting the checks required by GDPR, DORA and the AI Act.
- Policy
- Audit
- AI Act
Getting started
From use case to production, one step at a time.
We start where you are. Each phase ends with a verifiable result before moving on to the next.
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AI data assessment
Which data your AI projects need, where it lives, which of it is sensitive and which regulatory constraints apply.
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Proof of value
Delphix applied to a real use case: masked or synthetic data delivered to the team, with agreed KPIs.
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Production and managed services
Extension to more sources and teams, integration into data and MLOps pipelines, and ongoing platform support and management.
Responsible AI
Trust above all.
An AI project is only as good as the trust in the data that feeds it. That's why data protection comes before the model, not after.
- Regulation
- AI ActQuality, traceability and governance of the data used by AI systems.
- Personal data
- GDPRData minimization and pseudonymization in non-production environments.
- Financial sector
- DORAOperational resilience and data protection in test environments.
- Approach
- Privacy by designData masked before it leaves production.
Contact
Secure data for your AI.
A dataset to make compliant, a model to train on real data or a data platform to secure: write to us and we'll put you in touch with the right professional.
- Emailinfo@cogitatech.it